phd topics in bioinformatics

Tips & Tricks

Current research topics in bioinformatics.

Researchers working in the scientific area always want to explore new and hot topics to make informed choices. In this article, all new, current, and demanding research topics in bioinformatics are mentioned. This article is helpful for the researchers who are looking for trends in bioinformatics to select a research topic of broad-spectrum.

Since the research in bioinformatics and its applications

are exponentially increasing every year, it is essential to know hot topics for researchers who are trying to make a career in this area. Currently, most of the research is focused on treating deadly diseases such as “ cancer, coronary artery disease, HIV, chronic infections ”, and so on . In silico drug designing is always demanding in designing inhibitors or potential drugs for such diseases. Besides, a lot of scientists are working on next-generation sequencing, big data , and cancer . A recent study has found that the interest of researchers in these topics plateaued over after the early 2000s [1].

Besides the above mentioned hot topics, the following topics are considered demanding in bioinformatics.

• Cloud computing, big data, Hadoop
• Machine learning
• Artificial intelligence
• Functional genomics
• Rna-seq analysis (equally relevant along with next-generation sequencing techniques)
• Data mining (including text search, data integration, database development, and management)
• Neural networks
• Mathematical modeling
• Mirna function identification
• Evolutionary studies
• Genomics, transcriptomics, and proteomics
• Metabolomics

If you are new and trying to learn bioinformatics, then read the following articles:

• Bioinformatics- Where & How to Start?

List of Bioinformatics Books for Beginners

• Hahn A., Mohanty S.D., Manda P. (2017) What’s Hot and What’s Not? – Exploring Trends in Bioinformatics Literature Using Topic Modeling and Keyword Analysis. In: Cai Z., Daescu O., Li M. (eds) Bioinformatics Research and Applications. ISBRA 2017. Lecture Notes in Computer Science, vol 10330. Springer, Cham. https://doi.org/10.1007/978-3-319-59575-7_25

Careers in Bioinformatics and Computational Biology

Md simulation using gromacs: things to remember.

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Education & Training

Phd in bioinformatics and systems biology with emphasis in biomedical informatics.

The PhD curriculum for our trainees consists of formal instruction to provide the intellectual framework for conducting research.

Biomedical Informatics Core

• Informatics in Clinical Environments (MED 265): 1 Students are introduced to the basics of healthcare systems and clinical information needs through direct observation and classroom discussion. Students are introduced to medical language, disease processes, and health care practices to provide context prior to direct patient observation at primary, specialty, emergency, and inpatient sites in conjunction with clinical faculty affiliated with the training program. Students examine how clinicians use history-taking, physical examination and diagnostic testing to establish diagnoses and prognoses. Medical decision-making is introduced in the context of available informatics tools and clinical documentation and communication processes. Post-observation classroom discussions encourage students to think critically of the processes they observed and formulate hypotheses about how informatics solutions can modify the processes.
• Modeling Clinical Data and Knowledge for Computation (MED 267): This course describes existing methods for representing and communicating biomedical knowledge. The course describes existing health care standards and modeling principles required for implementing data standards, including biomedical ontologies, standardized terminologies, and knowledge resources.

1  Students with a clinical background will replace MED 265 with an additional course: Bioinformatics Applications to Human Disease (MED 263).

Bioinformatics Core

The core courses provide foundations in the biological basis of human health and disease and the statistical discovery of medical knowledge from biological experimentation. These classes are taken during the first year.

• Bioinformatics II (BENG 202) :  Introduction to methods for sequence analysis, applications to genome and proteome sequences, and protein structure and sequence-structure analysis.
• Principles of Biomedical Informatics (MED 264) : students are introduced to the fundamental principles of BMI and to the problems that define modern healthcare. The extent to which BMI can address healthcare problems is explored. Topics covered include structuring of data, computing with phenotypes, integration of molecular, image and other non-traditional data types into electronic medical records, clinical decision support systems, biomedical ontologies, data and communication standards, data aggregation, and knowledge discovery.
• Bioinformatics IV (MATH 283):  Analysis of modern genomic data, sequence analysis, gene expression/functional genomics analysis, and gene mapping/applied population genetics. The course focuses on statistical modeling and inference.

For the fourth core class, choose one of the following. In the event that a student completes two or more of these with suitable grades, one will count as core and the other(s) as electives.

• Algorithms in Computational Biology (CSE 280A): (Formerly CSE 206B) The course focuses on algorithmic aspects of modern bioinformatics and covers the following topics: computational gene hunting, sequencing, DNA arrays, sequence comparison, pattern discovery in DNA, genome rearrangements, molecular evolution, computational proteomics, and others. Prerequisites: CSE202 preferred or consent of instructor. 
• Algorithms for Biological Data Analysis (ECE 208): This course introduces a series of general algorithmic techniques but uses computational evolutionary biology as the context. The course motivates each algorithmic concept using a specific biological application related to evolution and focuses the discussion on specific types of (big) data available in modern biological studies. Note: The instructor and the BISB program are in the process of getting approval from the Graduate Council to introduce this as a course and to allow it as a core option. While we await approval, the course is offered under a temporary course number, ECE 286, by Prof. Siavash Mirarab, with the title "Algorithms for Biological Data Analysis." The course code ECE 286 may be used by other special topics courses as well, so be sure to enroll in the correct one.
• Genomics, Proteomics, and Network Biology (Bioinformatics III, BENG 203/CSE283): This is core in the BISB track. In the BMI track, it may be taken as the 4th core class or as an elective. Anotating genomes, characterizing functional genes, profiling, reconstructioning pathways.  Prerequisites: Pharm 201, BENG 202/CSE282, or consent of instructor. 

All students in years 1 and 2 must take both seminars in fall, winter, and spring quarters.

• Current Trends in Biomedical Informatics (MED 262): Weekly talks by researchers introduce students to current research topics within BMI. Speakers are drawn from academia, health care organizations, industry, and government.
• Bioinformatics Student Research Talks (BNFO 283) : Weekly presentations by Bioinformatics and Systems Biology students about Research Projects that are proposed or completed. Faculty mentors are present to contribute critiques and suggestions.

All students must take one of the two ethics courses by the end of second year. However, funding sources may require that it be taken first year, so we recommend taking it the first year.

• Scientific Ethics (SOMI 226): see below description
• Ethics in Scientific Research (BIOM 219): Overview of ethical issues in scientific research, conflicts of interest; national, statewide and campus issues and requirement; ethical issues in publications; authorship; retention of research records; tracing of research records; attribution; plagiarism; copyright considerations; primary, archival and meeting summary publications; ethical procedures and policies; NIH, NSF, California and UC San Diego; case studies and precedents in ethics.

Research and Teaching

During the academic year, all students must be enrolled in the appropriate research course for their level. Students typically do three rotations in year 1 (BNFO 298) and then do research units (BNFO 299) with their thesis advisor in years 2 and later. BNFO 299 units may be varied to meet the full-time enrollment requirement of 12 units per quarter in fall, winter, and spring.

• Teaching Assistantship (TA) (BNFO 500) :  Students will be a TA for two quarters during second or third year. To prepare for this teaching, students will receive training through the Center for Teaching Development at UCSD.
• Research Rotation (BNFO 298) : Taken each quarter during first year to help determine the thesis adviser.
• Graduate Research (BNFO 299): Independent work by graduate students engaged in research and writing theses. S/U grades only. May be taken for credit fifteen times.

Students must take 16 units of elective courses, including 8 units from the BMI series and 4 units from the CS series. The final 4 units can be taken from any series. The two BMI core courses MED 265 (or MED 263 for students with a clinical background) and MED 267 count as electives. Please check this  BISB curriculum page  for the list of all approved electives and elective series. 

Formal Progress to Degree

There are three formal evaluations that students must complete prior to being awarded a PhD degree: 

• Qualifying Examination:  This examination must be passed prior to the end of the student’s second year of study. The written portion of the exam consists of the student preparing an NIH or NSF-style research proposal. This proposal is then defended in an oral examination. Once the student passes the oral portion of the exam, the student is deemed to be qualified for advancing into PhD thesis research.
• Advancement to PhD Candidacy:  Upon completion of formal course requirements, each student is required to take a written and oral qualifying examination that admits the student to the candidacy of the PhD Program. The exam is administered by the dissertation committee, which consists of five faculty members.
• Final Examination:  All students defend their thesis in a final oral examination.

How to Apply

Application for admission to graduate studies is made directly through the Bioinformatics and Systems Biology website.

To be considered for the NLM fellowship, in addition to submitting your application and documentation to the degree program of your choice, please send the following to dbmi fellowship at ucsd dot edu:

• Personal Statement- explaining why you are a good candidate for the fellowship and what you hope to accomplish as an NLM trainee, the specific kind of research and topics you are interested in studying and what your goals are after completing the fellowship.
• A current and up to date CV; and
• In the body of your email please indicate which degree program you are applying to.

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Center for Computational Biology

Computational Biology PhD

The main objective of the Computational Biology PhD is to train the next generation of scientists who are both passionate about exploring the interface of computation and biology, and committed to functioning at a high level in both computational and biological fields.

The program emphasizes multidisciplinary competency, interdisciplinary collaboration, and transdisciplinary research, and offers an integrated and customizable curriculum that consists of two semesters of didactic course work tailored to each student’s background and interests, research rotations with faculty mentors spanning computational biology’s core disciplines, and dissertation research jointly supervised by computational and biological faculty mentors.

The Computational Biology Graduate Group facilitates student immersion into UC Berkeley’s vibrant computational biology research community. Currently, the Group includes over 46 faculty from across 14 departments of the College of Letters and Science, the College of Engineering, the College of Natural Resources, and the School of Public Health. Many of these faculty are available as potential dissertation research advisors for Computational Biology PhD students, with more available for participation on doctoral committees.

The First Year

The time to degree (normative time) of the Computational Biology PhD is five years. The first year of the program emphasizes gaining competency in computational biology, the biological sciences, and the computational sciences (broadly construed). Since student backgrounds will vary widely, each student will work with faculty and student advisory committees to develop a program of study tailored to their background and interests. Specifically, all first-year students must:

• Perform three rotations with Core faculty (one rotation with a non-Core faculty is acceptable with advance approval)
• Complete course work requirements (see below)
• Complete a course in the Responsible Conduct of Research
• Attend the computational biology seminar series
• Complete experimental training (see below)

Laboratory Rotations

Entering students are required to complete three laboratory rotations during their first year in the program to seek out a Dissertation Advisor under whose supervision dissertation research will be conducted. Students should rotate with at least one computational Core faculty member and one experimental Core faculty member. Click here to view rotation policy. 

Course Work & Additional Requirements

Students must complete the following coursework in the first three (up to four) semesters. Courses must be taken for a grade and a grade of B or higher is required for a course to count towards degree progress:

• Fall and Spring semester of CMPBIO 293, Doctoral Seminar in Computational Biology
• A Responsible Conduct of Research course, most likely through the Department of Molecular and Cell Biology.
• STAT 201A & STAT 201B : Intro to Probability and Statistics at an Advanced Level. Note: Students who are offered admission and are not prepared to complete STAT 201A and 201B will be required to complete STAT 134 or PH 142 first.
• CS61A : The Structure and Interpretation of Computer Programs. Note: students with the equivalent background can replace this requirement with a more advanced CS course of their choosing.
• 3 elective courses relevant to the field of Computational Biology , one of which must be at the graduate level (see below for details).
• Attend the computational biology invited speaker seminar series. A schedule is circulated to all students by email and is available on the Center website. Starting with the 2023 entering class, CCB PhD students must enroll in CMPBIO 275: Computational Biology Seminar , which provides credit for this seminar series.
• 1) completion of a laboratory course at Berkeley with a minimum grade of B,
• 2) completion of a rotation in an experimental lab (w/ an experimental project), with a positive evaluation from the PI,
• a biological sciences undergraduate major with at least two upper division laboratory-based courses,
• a semester or equivalent of supervised undergraduate experimental laboratory-based research at a university,
• or previous paid or volunteer/internship work in an industry-based experimental laboratory.

Students are expected to develop a course plan for their program requirements and to consult with the Head Graduate Advisor before the Spring semester of their first year for formal approval (signature required). The course plan will take into account the student’s undergraduate training areas and goals for PhD research areas.

Satisfactory completion of first year requirements will be evaluated at the end of the spring semester of the first year. If requirements are satisfied, students will formally choose a Dissertation advisor from among the core faculty with whom they rotated and begin dissertation research.

Waivers: Students may request waivers for the specific courses STAT 201A, STAT 201B, and CS61A. In all cases of waivers, the student must take alternative courses in related areas so as to have six additional courses, as described above. For waiving out of STAT 201A/B, students can demonstrate they have completed the equivalent by passing a proctored assessment exam on Campus. For waiving out CS61A, the Head Graduate Advisor will evaluate student’s previous coursework based on the previous course’s syllabus and other course materials to determine equivalency.

Electives: Of the three electives, students are required to choose one course in each of the two following cluster areas:

• Cluster A (Biological Science) : These courses are defined as those for which the learning goals are primarily related to biology. This includes courses covering topics in molecular biology, genetics, evolution, environmental science, experimental methods, and human health. This category may also cover courses whose focus is on learning how to use bioinformatic tools to understand experimental data.
• Cluster B (Computational Sciences): These courses are defined as those for which the learning goals involve computing, inference, or mathematical modeling, broadly defined. This includes courses on algorithms, computing languages or structures, mathematical or probabilistic concepts, and statistics. This category would include courses whose focus is on biological applications of such topics.

In the below link we give some relevant such courses, but students can take courses beyond this list; for courses not on this list, the Head Graduate Advisor will determine to which cluster a course can be credited. For classes that have significant overlap between these two clusters, the department which offers the course may influence the decision of the HGA as to whether the course should be assigned to cluster A or B.

See below for some suggested courses in these categories:

Suggested Coursework Options

Second Year & Beyond

At the beginning of the fall of the second year, students begin full-time dissertation research in earnest under the supervision of their Dissertation advisor. It is anticipated that it will take students three (up to four) semesters to complete the 6 course requirement. Students are required to continue to participate annually in the computational biology seminar series.

Qualifying Examination

Students are expected to take and pass an oral Qualifying Examination (QE) by the end of the spring semester (June 15th) of their second year of graduate study. Students must present a written dissertation proposal to the QE committee no fewer than four weeks prior to the oral QE. The write-up should follow the format of an NIH-style grant proposal (i.e., it should include an abstract, background and significance, specific aims to be addressed (~3), and a research plan for addressing the aims) and must thoroughly discuss plans for research to be conducted in the dissertation lab. Click here for more details on the guidelines and format for the QE. Click here to view the rules for the composition of the committee and the form for declaring your committee.

Advancement to Candidacy

After successfully completing the QE, students will Advance to Candidacy. At this time, students select the members of their dissertation committee and submit this committee for approval to the Graduate Division. Students should endeavor to include a member whose research represents a complementary yet distinct area from that of the dissertation advisor (ie, biological vs computational, experimental vs theoretical) and that will be integrated in the student’s dissertation research. Click here to view the rules for the composition of the committee and the form for declaring your committee.

Meetings with the Dissertation Committee

After Advancing to Candidacy, students are expected to meet with their Dissertation Committee at least once each year.

Teaching Requirements

Computational Biology PhD students are required to teach at least two semesters (starting with Fall 2019 class), but may teach more. The requirement can be modified if the student has funding that does not allow teaching. Starting with the Fall 2019 class: At least one of those courses should require that you teach a section. Berkeley Connect or CMPBIO 293 can count towards one of the required semesters.

The Dissertation

Dissertation projects will represent scholarly, independent and novel research that contributes new knowledge to Computational Biology by integrating knowledge and methodologies from both the biological and computational sciences. Students must submit their dissertation by the May Graduate Division filing deadline (see Graduate Division for date) of their fifth–and final–year.

Special Requirements

Students will be required to present their research either orally or via a poster at the annual retreat beginning in their second year.

• Financial Support

The Computational Biology Graduate Group provides a competitive stipend as well as full payment of fees and non-resident tuition (which includes health care). Students maintaining satisfactory academic progress are provided full funding for five to five and a half years. The program supports students in the first year, while the PI/mentor provides support from the second year on. A portion of this support is in the form of salary from teaching assistance as a Graduate Student Instructor (GSI) in allied departments, such as Molecular and Cell Biology, Integrative Biology, Plant and Microbial Biology, Mathematics, Statistics or Computer Science. Teaching is part of the training of the program and most students will not teach more than two semesters, unless by choice.

Due to cost constraints, the program admits few international students; the average is two per year. Those admitted are also given full financial support (as noted above): stipend, fees and tuition.

Students are also strongly encouraged to apply for extramural fellowships for the proposal writing experience. There are a number of extramural fellowships that Berkeley students apply for that current applicants may find appealing. Please note that the NSF now only allows two submissions – once as an undergrad and once in grad school. The NSF funds students with potential, as opposed to specific research projects, so do not be concerned that you don’t know your grad school plans yet – just put together a good proposal! Although we make admissions offers before the fellowships results are released, all eligible students should take advantage of both opportunities to apply, as it’s a great opportunity and a great addition to a CV.

• National Science Foundation Graduate Research Fellowship (app deadlines in Oct)
• Hertz Foundation Fellowship (app deadline Oct)
• National Defense Science and Engineering Graduate Fellowship (app deadline in mid-Fall)
• DOE Computational Science Graduate Fellowship (Krell Institute) (app deadline in Jan)

CCB no longer requires the GRE for admission (neither general, nor subject). The GRE will not be seen by the review committee, even if sent to Berkeley.

PLEASE NOTE: The application deadline is Monday, December 2 , 2024, 8:59 PST/11:59 EST

We invite applications from students with distinguished academic records, strong foundations in the basic biological, physical and computational sciences, as well as significant computer programming and research experience. Admission for the Computational Biology PhD is for the fall semester only, and Computational Biology does not offer a Master’s degree.

We are happy to answer any questions you may have, but please be sure to read this entire page first, as many of your questions will be answered below or on the Tips tab.

IMPORTANT : Please note that it is not possible to select a specific PhD advisor until the end of the first year in the program, so contacting individual faculty about openings in their laboratories will not increase your chances of being accepted into the program. You will have an opportunity to discuss your interests with relevant faculty if you are invited to interview in February.

Undergraduate Preparation

Minimum requirements for admission to graduate study:

• A bachelor’s degree or recognized equivalent from an accredited institution.
• Minimum GPA of 3.0.
• Undergraduate preparation reflecting a balance of training in computational biology’s core disciplines (biology, computer science, statistics/mathematics), for example, a single interdisciplinary major, such as computational biology or bioinformatics; a major in a core discipline and a combination of interdisciplinary course work and research experiences; or a double major in core disciplines.
• Basic research experience and aptitude are key considerations for admission, so evidence of research experience and letters of recommendation from faculty mentors attesting to the applicant’s research experience are of particular interest.
• GRE – NOT required or used for review .
• TOEFL scores for international students (see below for details).

Application Requirements

ALL materials, including letters, are due December 2, 2024 (8:59 PST). More information is provided and required as part of the online application, so please create an account and review the application before emailing with questions (and please set up an account well before the deadline):

• A completed graduate application: The online application opens in early or mid-September and is located on the Graduate Division website . Paper applications are not accepted. Please create your account and review the application well ahead of the submit date , as it will take time to complete and requests information not listed here.
• A nonrefundable application fee: The fee must be paid using a major credit card and is not refundable. For US citizens and permanent residents, the fee is $135; US citizens and permanent residents may request a fee waiver as part of the online application. For all other students (international) the fee is $155 (no waivers, no exceptions). Graduate Admissions manages the fee, not the program, so please contact them with questions.
• Three letters of recommendation, minimum (up to five are accepted): Letters of recommendation must be submitted online as part of the Graduate Division’s application process. Letters are also due Dec. 2, so please inform your recommenders of this deadline and give them sufficient advance notice. It is your responsibility to monitor the status of your letters of recommendation (sending prompts, as necessary) in the online system.
• Transcripts: Unofficial copies of all relevant transcripts, uploaded as part of the online application (see application for details). Scanned copies of official transcripts are strongly preferred, as transcripts must include applicant and institution name and degree goal and should be easy for the reviewers to read (print-outs from online personal schedules can be hard to read and transcripts without your name and the institution name cannot be used for review). Do not send via mail official transcripts to Grad Division or Computational Biology, they will be discarded.
• Essays: Follow links to view descriptions of what these essays should include ( Statement of Purpose [2-3 pages], Personal Statement [1-2 pages]). Also review Tips tab for formatting advice.
• (Highly recommended) Applicants should consider applying for extramural funding, such as NSF Fellowships. These are amazing opportunities and the application processes are great preparation for graduate studies. Please see Financial Support tab.
• Read and follow all of the “Application Tips” listed on the last tab. This ensures that everything goes smoothly and you make a good impression on the faculty reviewing your file.

The GRE general test is not required. GRE subject tests are not required. GRE scores will not be a determining factor for application review and admission, and will NOT be seen by the CCB admissions committee. While we do not encourage anyone to take the exam, in case you decide to apply to a different program at Berkeley that does require them: the UC Berkeley school code is 4833; department codes are unnecessary. As long as the scores are sent to UC Berkeley, they will be received by any program you apply to on campus.

TOEFL/IELTS

Adequate proficiency in English must be demonstrated by those applicants applying from countries where English is not the official language. There are two standardized tests you may take: the Test of English as a Foreign Language (TOEFL), and the International English Language Testing System (IELTS). TOEFL minimum passing scores are 90 for the  Internet-based test (IBT) , and 570 for the paper-based format (PBT) . The TOEFL may be waived if an international student has completed at least one year of full-time academic course work with grades of B or better while in residence at a U.S. university (transcript will be required). Please click here for more information .

Application Deadlines

The Application Deadline is 8:59 pm Pacific Standard Time, December 2, 2024 . The application will lock at 9pm PST, precisely. All materials must be received by the deadline. While rec letters can continue to be submitted and received after the deadline, the committee meets in early December and will review incomplete applications. TOEFL tests should be taken by or before the deadline, but self-reported scores are acceptable for review while the official scores are being processed. All submitted applications will be reviewed, even if materials are missing, but it may impact the evaluation of the application.

It is your responsibility to ensure and verify that your application materials are submitted in a timely manner. Please be sure to hit the submit button when you have completed the application and to monitor the status of your letters of recommendation (sending prompts, as necessary). Please include the statement of purpose and personal statement in the online application. While you can upload a CV, please DO NOT upload entire publications or papers. Please DO NOT send paper résumés, separate folders of information, or articles via mail. They will be discarded unread.

The Computational Biology Interview Visit dates are yet to be determined, but will be posted here once they are.

Top applicants who are being considered for admission will be invited to visit campus for interviews with faculty. Invitations will be made by early January. Students are expected to stay for the entire event, arriving in Berkeley by 5:30pm on the first day and leaving the evening of the final day. In the application, you must provide the names of between 7-10 faculty from the Computational Biology website with whom you are interested in conducting research or performing rotations. This helps route your application to our reviewers and facilitates the interview scheduling process. An invitation is not a guarantee of admission.

International students may be interviewed virtually, as flights are often prohibitively expensive.

Tips for the Application Process

Uploaded Documents: Be sure to put your name and type of essay on your essays ( Statement of Purpose [2-3 pages], Personal Statement [1-2 pages]) as a header or before the text, whether you use the text box or upload a PDF or Word doc. There is no minimum length on either essay, but 3 pages maximum is suggested. The Statement of Purpose should describe your research and educational background and aspirations. The Personal Statement can include personal achievements not necessarily related to research, barriers you’ve had to overcome, mentoring and volunteering activities, things that make you unique and demonstrate the qualities you will bring to the program.

Letters of Recommendation: should be from persons who have supervised your research or academic work and who can evaluate your intellectual ability, creativity, leadership potential and promise for productive scholarship. If lab supervision was provided by a postdoc or graduate student, the letter should carry the signature or support of the faculty member in charge of the research project. Note: the application can be submitted before all of the recommenders have completed their letters. It is your responsibility to keep track of your recommender’s progress through the online system. Be sure to send reminders if your recommenders do not submit their letters.

Extramural fellowships: it is to your benefit to apply for fellowships as they may facilitate entry into the lab of your choice, are a great addition to your CV and often provide higher stipends. Do not allow concerns about coming up with a research proposal before joining a lab prevent you from applying. The fellowships are looking for research potential and proposal writing skills and will not hold you to specific research projects once you have started graduate school.

Calculating GPA: Schools can differ in how they assign grades and calculate grade point averages, so it may be difficult for this office to offer advice. The best resource for calculating the GPA for your school is to check the back of the official transcripts where a guide is often provided or use an online tool. There are free online GPA conversion tools that can be found via an internet search.

Faculty Contact/Interests: Please be sure to list faculty that interest you as part of the online application. You are not required to contact any faculty in advance, nor will it assist with admission, but are welcome to if you wish to learn more about their research.

Submitting the application: To avoid the possibility of computer problems on either side, it is NOT advisable to wait until the last day to start and/or submit your application. It is not unusual for the application system to have difficulties during times of heavy traffic. However, there is no need to submit the application too early. No application will be reviewed before the deadline.

Visits: We only arrange one campus visit for recruitment purposes. If you are interested in visiting the campus and meeting with faculty before the application deadline, you are welcome to do so on your own time (we will be unable to assist).

Name: Please double check that you have entered your first and last names in the correct fields. This is our first impression of you as a candidate, so you do want to get your name correct! Be sure to put your name on any documents that you upload (Statement of Purpose, Personal Statement).

California Residency: You are not considered a resident if you hope to enter our program in the Fall, but have never lived in California before or are here on a visa. So, please do not mark “resident” on the application in anticipation of admission. You must have lived in California previously, and be a US citizen or Permanent Resident, to be a resident.

Faculty Leadership Head Graduate Advisor and Chair for the PhD & DE John Huelsenbeck ( [email protected] )

Associate Head Graduate Advisor for PhD & DE Liana Lareau ( [email protected] )

Equity Advisor Rasmus Nielsen ( [email protected] )

Director of CCB Elizabeth Purdom ( [email protected] )

Core PhD & DE Faculty ( link )

Staff support Student Services Advisor (GSAO): Kate Chase ( [email protected] )

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An all-encompassing, highly interdisciplinary field

Program Overview

The University of Michigan  Bioinformatics Graduate Program builds a strong foundation for Master’s and PhD students through comprehensive course offering, research training and mentoring.

Students in our program take courses in advanced math, modeling, statistics, computer programming, machine learning, informatics, comprehensive courses in introductory biology, genomics, proteomics, clinical informatics, environmental health, and much more. They are encouraged to take advantage of the enormous research and teaching resources across U-M.

Our students have an abundance of research opportunities in many subject areas under the mentorship of our 130 affiliated faculty members of the Center for Computational Medicine and Bioinformatics ( CCMB ). These faculty are from U-M Medical School, College of Engineering, College of Literature, Arts and Sciences, School of Public Health, School of Nursing, and School of Information. 

In 2023, the Bioinformatics Graduate Program maintains a student body of 87 PhD students, and over 120 Master's students. They are mentored by the 44 DCMB faculty and the 130 CCMB faculty. Faculty members with biological and more quantitative expertise are both well represented.

The Bioinformatics Graduate Program was created in 1999 and is housed in the Department of Computational Medicine and Bioinformatics ( DCMB ). 

Apply through our PIBS application

Bioinformatics offers an extensive range of research opportunities, from applications for clinical medical problems and specific diseases to computational work on synthetic biological systems. There are very active groups in:

• Artificial Intelligence (AI) and machine learning
• Genomics, regulatory genomics and epigenomics
• Protein structure, proteomics, and alternative splicing
• Multi-“omics” integrative bioinformatics
• Systems biology and networks analysis
• Biomedical data science, translational bioinformatics and pharmacogenomics
• Methodological development in computational biology
• Applications to complex genetic diseases
• 4D Nucleome
• Single Cell Analysis
• Signal/Image Processing and Machine Learning

Bioinformatics has had NIH supported training grants since 2005. Our students are eligible for a wide range of other training grant support related to more specific areas of research, such as genomics or cancer proteomics.

Students are required to take courses in each of the following areas:

• Introductory Bioinformatics
• Computing & Informatics
• Probability & Statistics
• Molecular Biology
• Bioinformatics 602 (Journal Club) taken once in the first year.
• Bioinformatics 603 (Journal Club) taken once; students present papers for discussion
• Research Responsibility and Ethics course (PIBS 503)
• One Advanced Bioinformatics course offered or cross-listed by the Bioinformatics Graduate Program
• One additional Advanced Bioinformatics course in any program

Details about courses available in each of these areas can be found on the department website . Courses may be offered by Bioinformatics or other units.

Attendance at weekly seminars is also expected. Offered seminars include a weekly series of invited guest speakers, “Tools & Tech” presentations that highlight a tool or technology, either under development or in current use, and BISTRO, a lively seminar where students present their ongoing research.

Preliminary Examination

Students take a preliminary exam in their second year, usually at the end of the 3rd or 4th term. The preliminary exam should show both creativity and skill, and should not be identical to the student’s thesis work. The aims of the examination are two-fold. The first aim is to demonstrate that students have developed the ability to analyze a scientific problem and develop appropriate strategies to carry out a research plan. The second aim is to demonstrate that students have enough Bioinformatics knowledge needed to carry out their thesis research. Students sometimes develop their prelim proposals into a paper and/or a thesis chapter later.

Teaching Requirement

Teaching, in Bioinformatics or in other departments, is encouraged and expected for at least one term from most Bioinformatics students. Individual circumstances such as English language ability, interest, and funding situation of the mentor are considered.

Expected Length of Program

The expected time to PhD graduation is 5 to 6 years.

Approximately 8-15 new students join the PhD program each year. Each term, contact between faculty and students is encouraged through research events & social gatherings. Given the interdisciplinary nature of the program, students are encouraged to develop and pursue their own research interests. In an effort to support students’ academic growth, the department and other units (such as Rackham Graduate School) offer funding to assist students with conference participation or workshop attendance.

Approximately 50% of program alumni choose academia, while others with go into industry with many working at biotechnology companies. Aware of this, current students are provided opportunities to meet with guest seminar speakers or visitors from industry. In addition, outside internships are encouraged if related to a student’s research as they have proven to be valuable experiences.

The program supports student-led initiatives that are focused on building community such as student organized social activities, a pre-Thanksgiving dinner, and group run in the local marathon. Separately, Bioinformatics coordinates an annual off-site weekend retreat and an annual picnic.

DCMB welcomes and supports several  student organizations :

• The Bioinformatics Graduate Student Association (BGSA)
• The Bioinformatics Black Student Union (BBSU)
• The Data Analysis Networking Group (DANG!)
• DCMB Girls Who Code Club

Alumni from the Bioinformatics Graduate Program pursue successful careers in academia, biotechnology and biomedical research in industry and government. Most of them are employed immediately after graduation.

Learn more about the Department of Computational Medicine and Bioinformatics.

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Computational and Systems Biology PhD Program

Computational and systems biology.

The field of computational and systems biology represents a synthesis of ideas and approaches from the life sciences, physical sciences, computer science, and engineering. Recent advances in biology, including the human genome project and massively parallel approaches to probing biological samples, have created new opportunities to understand biological problems from a systems perspective. Systems modeling and design are well established in engineering disciplines but are newer in biology. Advances in computational and systems biology require multidisciplinary teams with skill in applying principles and tools from engineering and computer science to solve problems in biology and medicine. To provide education in this emerging field, the Computational and Systems Biology (CSB) program integrates MIT's world-renowned disciplines in biology, engineering, mathematics, and computer science. Graduates of the program are uniquely prepared to make novel discoveries, develop new methods, and establish new paradigms. They are also well-positioned to assume critical leadership roles in both academia and industry, where this field is becoming increasingly important.

Computational and systems biology, as practiced at MIT, is organized around "the 3 Ds" of description, distillation, and design. In many research programs, systematic data collection is used to create detailed molecular- or cellular-level descriptions of a system in one or more defined states. Given the complexity of biological systems and the number of interacting components and parameters, system modeling is often conducted with the aim of distilling the essential or most important subsystems, components, and parameters, and of obtaining simplified models that retain the ability to accurately predict system behavior under a wide range of conditions. Distillation of the system can increase the interpretability of the models in relation to evolutionary and engineering principles such as robustness, modularity, and evolvability. The resulting models may also serve to facilitate rational design of perturbations to test understanding of the system or to change system behavior (e.g., for therapeutic intervention), as well as efforts to design related systems or systems composed of similar biological components.

CSB Faculty and Research

More than 70 faculty members at the Institute participate in MIT's Computational and Systems Biology Initiative (CSBi). These investigators span nearly all departments in the School of Science and the School of Engineering, providing CSB students the opportunity to pursue thesis research in a wide variety of different laboratories. It is also possible for students to arrange collaborative thesis projects with joint supervision by faculty members with different areas of expertise. Areas of active research include computational biology and bioinformatics, gene and protein networks, regulatory genomics, molecular biophysics, instrumentation engineering, cell and tissue engineering, predictive toxicology and metabolic engineering, imaging and image informatics, nanobiology and microsystems, biological design and synthetic biology, neurosystems biology, and cancer biology.

The CSB PhD Program

The CSB PhD program is an Institute-wide program that has been jointly developed by the Departments of Biology, Biological Engineering, and Electrical Engineering and Computer Science. The program integrates biology, engineering, and computation to address complex problems in biological systems, and CSB PhD students have the opportunity to work with CSBi faculty from across the Institute. The curriculum has a strong emphasis on foundational material to encourage students to become creators of future tools and technologies, rather than merely practitioners of current approaches. Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged.

CSB Graduate Education

All students pursue a core curriculum that includes classes in biology and computational biology, along with a class in computational and systems biology based on the scientific literature. Advanced electives in science and engineering enhance both the breadth and depth of each student's education. During their first year, in addition to coursework, students carry out rotations in multiple research groups to gain a broader exposure to work at the frontier of this field, and to identify a suitable laboratory in which to conduct thesis research. CSB students also serve as teaching assistants during one semester in the second year to further develop their teaching and communication skills and facilitate their interactions across disciplines. Students also participate in training in the responsible conduct of research to prepare them for the complexities and demands of modern scientific research. The total length of the program, including classwork, qualifying examinations, thesis research, and preparation of the thesis is roughly five years.

The CSB curriculum has two components. The first is a core that provides foundational knowledge of both biology and computational biology. The second is a customized program of electives that is selected by each student in consultation with members of the CSB graduate committee. The goal is to allow students broad latitude in defining their individual area of interest, while at the same time providing oversight and guidance to ensure that training is rigorous and thorough.

Core Curriculum

The core curriculum consists of three classroom subjects plus a set of three research rotations in different research groups. The classroom subjects fall into three areas described below.

Modern Biology (One Subject): A term of modern biology at MIT strengthens the biology base of all students in the program. Subjects in biochemistry, genetics, cell biology, molecular biology, or neurobiology fulfill this requirement. The particular course taken by each student will depend on their background and will be determined in consultation with graduate committee members.

Computational Biology (One Subject): A term of computational biology provides students with a background in the application of computation to biology, including analysis and modeling of sequence, structural, and systems data. This requirement can be fulfilled by 7.91[J] / 20.490[J] Foundations of Computational and Systems Biology.

Topics in Computational and Systems Biology (One Subject): All first-year students in the program participate in / 7.89[J] Topics in Computational and Systems Biology, an exploration of problems and approaches in the field of computational and systems biology through in-depth discussion and critical analysis of selected primary research papers. This subject is restricted to first-year PhD students in CSB or related fields in order to build a strong community among the class. It is the only subject in the program with such a limitation.

Research Group Rotations (Three Rotations): To assist students with lab selection and provide a range of research activities in computational and systems biology, students participate in three research rotations of one to two months' duration during their first year. Students are encouraged to gain experience in experimental and computational approaches taken across different disciplines at MIT.

Advanced Electives

The requirement of four advanced electives is designed to develop both breadth and depth. The electives add to the base of the diversified core and contribute strength in areas related to student interest and research direction. To develop depth, two of the four advanced electives must be in the same research area or department. To develop breadth, at least one of the electives must be in engineering and at least one in science. Each student designs a program of advanced electives that satisfies the distribution and area requirements in close consultation with members of the graduate committee.

Additional Subjects: As is typical for students in other doctoral programs at MIT, CSB PhD students may take classes beyond the required diversified core and advanced electives described above. These additional subjects can be used to add breadth or depth to the proposed curriculum, and might be useful to explore advanced topics relevant to the student's thesis research in later years. The CSB Graduate Committee works with each graduate student to develop a path through the curriculum appropriate for his or her background and research interests.

Training in the Responsible Conduct of Research: Throughout the program, students will be expected to attend workshops and other activities that provide training in the ethical conduct of research. This is particularly important in interdisciplinary fields such as computational and systems biology, where different disciplines often have very different philosophies and conventions. By the end of the fourth year, students will have had about 16 hours of training in the responsible conduct of research.

Qualifying Exams: In addition to coursework and a research thesis, each student must pass a written and an oral qualifying examination at the end of the second year or the beginning of the third year. The written examination involves preparing a research proposal based on the student's thesis research, and presenting the proposal to the examination committee. This process provides a strong foundation for the thesis research, incorporating new research ideas and refinement of the scope of the research project. The oral examination is based on the coursework taken and on related published literature. The qualifying exams are designed to develop and demonstrate depth in a selected area (the area of the thesis research) as well as breadth of knowledge across the field of computational and systems biology.

Thesis Research: Research will be performed under the supervision of a CSBi faculty member, culminating in the submission of a written thesis and its oral defense before the community and thesis defense committee. By the second year, a student will have formed a thesis advisory committee that they will meet with on an annual basis.

Ph.D. in Computational Biology and Bioinformatics

General info.

• Faculty working with students: 60
• Students: 29
• Part time study available: No
• Application Terms: Fall
• Application Deadline: December 2

Monica Franklin Program Coordinator CBB Graduate Program Duke University Box 90090 Durham, NC 27708

Phone: 919-668-1049

Email: [email protected]

Website:  https://medschool.duke.edu/education/biomedical-phd-programs/computational-biology-and-bioinformatics-program

Program Description

The mission of the Graduate Program in Computational Biology and Bioinformatics (CBB) is to train predoctoral students to become leaders at the interdisciplinary intersection of quantitative and biomedical sciences. The program provides rigorous training in quantitative approaches from computer science, statistics, mathematics, physics, and engineering that enable its students to successfully address contemporary challenges across biology and medicine.  CBB trains students who have an interest and aptitude in both the computational and biological sciences. During their time in the program, students develop expertise in one or more quantitative areas, as well as in the specific biological area on which their research focuses.

Certificate in CBB

For students enrolled in other Ph.D. or masters programs of participating departments, the program also offers the opportunity to pursue a certificate in CBB. Students qualify for a CBB certificate by successfully completing two core courses plus an additional CBB course. Registration for the Computational Biology seminar every semester except the semester of graduation is also required.

• Computational Biology and Bioinformatics: PhD Admissions and Enrollment Statistics
• Computational Biology and Bioinformatics: PhD Completion Rate Statistics
• Computational Biology and Bioinformatics: PhD Time to Degree Statistics
• Computational Biology and Bioinformatics: PhD Career Outcomes Statistics

Application Information

Application Terms Available:  Fall

Application Deadline:  December 2

Graduate School Application Requirements See the Application Instructions page for important details about each Graduate School requirement.

• Transcripts: Unofficial transcripts required with application submission; official transcripts required upon admission
• Letters of Recommendation: 3 Required
• Statement of Purpose: Required
• Résumé: Required
• GRE Scores: GRE General (Optional)
• English Language Exam: TOEFL, IELTS, or Duolingo English Test required* for applicants whose first language is not English *test waiver may apply for some applicants
• GPA: Undergraduate GPA calculated on 4.0 scale required

Department-Specific Application Requirements (submitted through online application)

Writing Sample None required

Additional Components Optional Video Essay: How would a Duke PhD training experience help you achieve your academic and professional goals? Max video length 2 minutes; record externally and provide URL in application.

We strongly encourage you to review additional department-specific application guidance from the program to which you are applying: Departmental Application Guidance

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Integrated Biomedical Sciences (IBS)

Genomics & bioinformatics phd program.

The PhD in Genomics and Bioinformatics is designed to develop research scientists who apply principles and methods in genomics and bioinformatics to the study of human diseases.

The PhD in Genomics and Bioinformatics provides research training areas that reflect GW faculty expertise which includes DNA/RNA sequence analysis, algorithm development, cloud computing optimization, informatics platform development, biomarker discovery, microbiome, retrovirology (HIV/AIDS), autism spectrum disorders, muscular dystrophies, cancer genomics, glycoinformatics, microRNA processing, protein trafficking, and dysregulation of mitochondrial functions. Faculty are drawn largely from the GW School of Medicine and Health Sciences and Children’s Research Institute of Children’s National Health System.

Students have access to the state of the art technologies in genomics, proteomics, microscopy, bioinformatics, pre-clinical drug trials and multi-site clinical trial networks. Resources include the GW  Genomics Core , the GW  Biorepository  resource of biospecimens and clinical data, the  McCormick Genomic  and Proteomic Center, and  Colonial One  (the GW High Performance Computing Cluster), as well as cutting-edge core facilities for flow cytometry, imaging, and pathology.

PhD programs in the biomedical sciences are designed to meet key goals in contemporary graduate research education including 1) discipline-specific knowledge, 2) research skill development, 3) research communication skills, 4) research leadership, 5) research professionalism, and prepare graduates for a variety of science careers. To apply, please visit  IBS Admissions .

The PhD in Genomics & Bioinformatics begins with interdisciplinary coursework in molecular, cellular, and systems biology in the first semester. In the second and third semester students take a comprehensive introduction to the conceptual and experimental underpinnings of computational biology, statistics, genetics, and DNA sequencing. Career development coursework in scientific writing, oral communication, and research ethics; and laboratory rotations offered through GW’s Integrated Biomedical Sciences curriculum. Following required laboratory rotations, students work with their research advisor and the Graduate Program Directors to complete remaining Genomics & Bioinformatics degree requirements, including the dissertation.

Genomics and Bioinformatics Core:

• GENO 8231: Introduction to Genomics, Proteomics, and Bioinformatics
• GENO 8232: Computational Biology and Bioinformatics - Principals and Practices
• GENO 6223: Bioinformatics
• GENO 6237: Proteomics & Biomarkers
• GENO 8998: Advanced Reading and Research Seminar Course
• GENO 8999: Dissertation Research

Some Suggested Electives:

• BIOC 6240: Next Gen Sequencing.
• PUBH 6277: Public Health Genomics
• BMSC 8219: Writing the Grant-Style Qualifier

Seminars/Journal Clubs:

CTSI-CN Informatics Seminar Series

Complete grant-style qualifier examination, advance to candidacy

Graduate Program Directors:

Ljubica Caldovic, PhD Assistant Research Professor of Genomics and Precision Medicine Children's National Health System; GWU [email protected]

Raja Mazumder, PhD Professor of Biochemistry and Molecular Medicine GWU, Ross Hall 540 [email protected]

How to apply  to the IBS and Genomics and Bioinformatics PhD Program For IBS Application Questions contact Colleen Kennedy, IBS Program Manager

PhD in Bioinformatics Data Science

A Ph.D. in Bioinformatics Data Science will train the next-generation of researchers and professionals who will play a key role in multi- and interdisciplinary teams, bridging life sciences and computational sciences. Students will receive training in experimental, computational and mathematical disciplines through their coursework and research. Students who complete this degree will be able to generate and analyze experimental data for biomedical research as well as develop physical or computational models of the molecular components that drive the behavior of the biological system.

Students must complete a minimum of 15 hours of coursework, plus 3 credit hours of seminar, 6 credit hours of research and 9 credit hours of doctoral dissertation. The Ph.D. requires a minimum of 33 credits. Students who are admitted directly after a B.S. degree will be required to complete up to 9 additional credits in order to fulfill the core curriculum in the following areas: Database Systems, Statistics, and Introduction to Discipline. In addition, if students entering the program with an M.S. degree are lacking equivalent prerequisites, they also will be required to complete courses in these three areas; however, these courses may fulfill the elective requirement in the Ph.D. program, if approved in the program of study.

Academic Load

PhD students holding research assistantships (or teaching) are considered full-time with 6 credit hours . Students without RA or TA  are considered full-time if enrolled in at least 9 credit hours or in sustaining credit. Those enrolled for fewer than 9 credit hours are considered part-time students. Generally, a maximum load is 12 graduate credit hours; however, additional credit hours may be taken with the approval of the student’s adviser and the Graduate College. A maximum course load in either summer or winter session is 7 credit hours. Permission must be obtained from the Graduate College to carry an overload in any session. 

Bioinformatics Data Science Courses

Students must take one course in each of the following areas (9 credits):

Prerequisites

Students must fulfill core curriculum in each of the following areas (3-9 credits):

Elective Courses

Students must take two courses to compliment their bioinformatics data science dissertation project (6 credits): 

See Elective courses

Students must take six semesters of seminar (three 0 credit; three 1 credit) and give a presentation during three semesters.

Other Requirements:

• Formation of Graduate Dissertation Committee
• Successful completion of Graduate Preliminary Exam
• Research on a significant scientific problem
• Successful completion of Ph.D. Candidacy Exam
• Successful completion of Dissertation Defense

Formation of Graduate Committee

The student needs to establish a Dissertation Committee within the first year of study. The Committee should consist of at least four faculty members, including the primary faculty advisor (serving as the Committee Chair), a secondary faculty advisor (in a complementary field to the primary advisor), a second faculty from the home department, and one CBCB affiliate faculty outside the Departments of the primary and secondary advisors or from outside the University. Students must complete the Dissertation Committee Formation form and submit to the Associate Director.

Students should convene their dissertation committee at least once every six months.

Preliminary Examination

The preliminary examination should be taken before the end of the fourth semester and will consist of an oral exam in subjects based on the Bioinformatics Data Science core.* In recognition of the importance of the core curriculum in providing a good test of the student’s knowledge, students must achieve a minimum 3.0 GPA in the core curriculum before taking the preliminary exam. Students will not be permitted to take the preliminary examination if the core grade requirements and cumulative GPA of 3.0 has not been achieved. The exam will be administered by the Preliminary Exam Committee , which will consist of one instructor from each of the three core courses. Each member of the Committee will provide a single grade (pass, conditional pass or fail) and the final grades will be submitted via the Results of Preliminary Exam Form :

• Pass . The student may proceed to the next stage of his/her degree training.
• Conditional pass . In the event that the examination committee feels that the student did not have an adequate background or understanding in one or more specific areas, the Preliminary Exam Committee will communicate the conditional pass to the student and must provide the student with specific requirements and guidelines for completing the conditional pass. The student must inform the Preliminary Exam Committee, the Graduate Program Director and Program Committee when these conditions have been completed. The Preliminary Exam Committee will then meet with the student to ensure all recommendations have been completed and whether a re-examination is necessary. If required, the re-examination will be done using the same format and prior to the beginning of the next academic semester. If the student still does not perform satisfactorily on this re-examination, he/she will then be recommended to the Graduate Affairs Committee for dismissal from the graduate program.
• Failure . This outcome would indicate that the Examination Committee considers the student incapable of completing degree training. The student’s academic progress will be reviewed by the Graduate Affairs Committee, who will make recommendations to the Program Director regarding the student’s enrollment status. The Program Director may recommend to the Graduate College that the student be dismissed from the Program immediately.

*Students who need to complete prerequisite courses may request a deadline extension for the preliminary and subsequently the candidacy examination. Requests must be submitted to the Graduate Program Committee prior to the start of the third semester.

Candidacy Exam

The candidacy examination must be completed by the end of the sixth semester of enrollment.* It requires a formal, detailed proposal be submitted to the Dissertation Committee and an oral defense of the student’s proposed research project. Upon the recommendation of the Dissertation Committee, the student may be admitted to candidacy for the Ph.D. degree. The stipulations for admission to doctoral candidacy are that the student has (i) completed one academic years of full-time graduate study in residence at the University of Delaware, (ii) completed all required courses with the exception of BINF865 and BINF969, (iii) passed the preliminary exams, (iv) demonstrated the ability to perform research, and (v) had a research project accepted by the Dissertation Committee. Within one week of the candidacy exam, complete and submit the Recommendation for Candidacy for Doctoral Degree form for details. A copy of the completed form should be given to the Associate Director.

*Students who need to complete prerequisite courses may request a deadline extension for the preliminary and subsequently the candidacy examination.  Requests must be submitted to the Graduate Program Committee prior to the start of the third semester.

Dissertation Exam

The dissertation examination of the Ph.D. program will involve the approval of the written dissertation and an oral defense of the candidate’s dissertation.  The written dissertation will be submitted to the Dissertation Committee and the CBCB office at least three weeks in advance of the oral defense date.  The oral defense date will be publicly announced at least two weeks prior to the scheduled date. The oral presentation will be open to the public and all members of the Bioinformatics Data Science program. The Dissertation Committee will approve the candidate’s dissertation. The student and the primary faculty advisor will be responsible for making all corrections to the dissertation document and for meeting all Graduate College deadlines.  Within one week of the dissertation defense, complete and submit the Certification of Doctoral Dissertation Defense Form. A copy of the completed form should be given to the Associate Director.

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	University of Southern California
	Aug 26, 2024   USC Catalogue 2022-2023     USC Catalogue 2022-2023 [ARCHIVED CATALOGUE] | The Department of Quantitative and Computational Biology offers a PhD in Computational Biology and Bioinformatics. The PhD in Computational Biology and Bioinformatics is awarded in conformity with the general requirements of the USC Graduate School. Study in the Computational Biology and Bioinformatics PhD program emphasizes original research that culminates in a doctoral dissertation. A separately published guide, available from the Department of Quantitative and Computational Biology, provides additional information on the topics listed below, along with other program policies. Application deadline: December 15 Course Requirements Students in the Computational Biology and Bioinformatics PhD program take graduate courses that cover topics from biology, computer science, mathematics, statistics and other disciplines. These courses guarantee a broad foundation in our field, and ensure students have sufficient scientific background and intellectual tools for success in research. A list of required courses can be found at the bottom of this page. Screening Procedure As per Graduate School requirements, all students in the Computational Biology and Bioinformatics PhD program undergo a screening procedure. This procedure consists of written tests taken by each cohort before the end of their first year. Advisement Each student in the Computational Biology and Bioinformatics PhD program is assigned an academic adviser from among the Department of Quantitative and Computational Biology’s faculty. This person will act as the student’s dissertation committee chair. Advisers are determined by the end of the first year based on shared research interests with the student. The primary role of the adviser is to guide the student as they work towards their dissertation. Qualifying Examination Students must pass a qualifying examination to advance to candidacy in the Computational Biology and Bioinformatics PhD program. The qualifying exam consists of a written part and an oral part. Both parts are evaluated by a faculty qualifying committee, which is formed separately for each student and is led by the student’s dissertation chair. Dissertation After advancing to candidacy, each student forms a faculty dissertation committee. Students work toward their dissertation research under the guidance of their adviser and with input from their dissertation committee. The dissertation committee meets annually to ensure appropriate degree progress. The central requirement of the doctorate is a dissertation based on the student’s original research that makes a substantial advance to scientific knowledge or technical capability in our field. Required Courses (30 units) BISC 593 Practicum in Teaching the Biological Sciences Units: 2 CSCI 570 Analysis of Algorithms Units: 4 MATH 505a Applied Probability Units: 3 MATH 541a Introduction to Mathematical Statistics Units: 3 QBIO 502 Molecular Biology for Quantitative Scientists Units: 4 QBIO 542 Seminar in Computational Biology Units: 1 * QBIO 547 Ethics and Professional Conduct in Computational Biology Units: 1 QBIO 577 Computational Molecular Biology Laboratory Units: 2 QBIO 578a Computational Molecular Biology Units: 3 QBIO 578b Computational Molecular Biology Units: 3 * Students register for QBIO 542 for 5 semesters. Elective Courses (6 units) Choose a minimum of 6 units from the following courses: BISC 502a Molecular Genetics and Biochemistry Units: 4 BISC 502b Molecular Genetics and Biochemistry Units: 4 BME 530 Introduction to Systems Biology Units: 4 CSCI 521 Optimization: Theory and Algorithms Units: 3 CSCI 559 Machine Learning I: Supervised Methods Units: 4 CSCI 567 Machine Learning Units: 4 CSCI 596 Scientific Computing and Visualization Units: 4 CSCI 670x Advanced Analysis of Algorithms Units: 4 MATH 502a Numerical Analysis Units: 3 MATH 505b Applied Probability Units: 3 MATH 555a Partial Differential Equations Units: 3 MATH 565a Ordinary Differential Equations Units: 3 PHYS 516 Methods of Computational Physics Units: 3 PHYS 518 Thermodynamics and Statistical Mechanics Units: 3 Research and Dissertation (4 units minimum) QBIO 794a Doctoral Dissertation Units: 2 QBIO 794b Doctoral Dissertation Units: 2 Students may register for additional units by using QBIO 790 or the remaining QBIO 794 courses. Computational Biology & Biomedical Informatics (PhD Program) Computational biology and bioinformatics (CB&B) is a rapidly developing multidisciplinary field. The systematic acquisition of data made possible by genomics and proteomics technologies has created a tremendous gap between available data and their biological interpretation. Given the rate of data generation, it is well recognized that this gap will not be closed with direct individual experimentation. Computational and theoretical approaches to understanding biological systems provide an essential vehicle to help close this gap. These activities include computational modeling of biological processes, computational management of large-scale projects, database development and data mining, algorithm development, and high-performance computing, as well as statistical and mathematical analyses. Programs of Study PhD - Doctor of Philosophy Yale Computational Biology and Bioinformatics Computational Biology and Bioinformatics Mark Gerstein Director of Graduate Studies [email protected] Steven Kleinstein Samantha Naziri Departmental Registrar [email protected] Admission Requirements Standardized testing requirements. GRE is not accepted. English Language Requirement TOEFL iBT or IELTS Academic is required of most applicants whose native language is not English. BBS requires a score of at least 600 on the paper version, 250 on the computer-based exam, and 100 on the internet-based exam. Please take the test no later than November and no earlier than 24 months prior to submitting your application. Use institution code 3987 when reporting your scores; you may enter any department code. You may be exempt from this requirement if you have received (or will receive) an undergraduate degree from a college or university where English is the primary language of instruction, and if you have studied in residence at that institution for at least three years. Admission Information The PhD program in Computational Biology and Bioinformatics participates in the Combined Program in the Biological and Biomedical Sciences (BBS) , and applicants interested in pursuing a degree in cell biology should apply to the Computational Biology and Biomedical Informatics Track within BBS. Academic Information Program Advising Guidelines GSAS Advising Guidelines Academic Resources Academic calendar. The Graduate School's academic calendar lists important dates and deadlines related to coursework, registration, financial processes, and milestone events such as graduation. Featured Resource Registration Information and Dates https://registration.yale.edu/ Students must register every term in which they are enrolled in the Graduate School. Registration for a given term takes place the semester prior, and so it's important to stay on top of your academic plan. The University Registrar's Office oversees the systems that students use to register. Instructions about how to use those systems and the dates during which registration occurs can be found on their registration website. Financial Information Phd stipend & funding. PhD students at Yale are normally fully-funded. During their programs, our students receive a twelve-month stipend to cover living expenses and a fellowship that covers the full cost of tuition and student healthcare. PhD Student Funding Overview Graduate Financial Aid Office PhD Stipends Health Award Tuition and Fees Alumni Insights Below you will find alumni placement data for our departments and programs. Biomedical Informatics > Education > PhD Program PhD Program in Biomedical Informatics Make your mark: Our PhD program in biomedical informatics — the first and only one of its kind in the State University of New York system — helps you develop the sought-after skills for academic and applied research careers in our rapidly expanding field. Prepare to Lead Growth in health-related industries, hospitals and other health care systems have spearheaded Buffalo’s recent economic renaissance. All require effective information management systems and technologies. That’s where you come into the picture and take your place — front and center. A PhD in biomedical informatics from UB prepares you to lead these organizations through complex information management challenges. With your advanced knowledge and skills, you’ll apply sophisticated tools and methods to help design new systems and applications. Best of all, thanks to our close partnerships with regional health care organizations, you don’t have to wait until you’ve earned your PhD to begin making high-level contributions to our field: You’ll forge those connections and collaborations while training with us. Specialize with the Experts We offer you a broad-based curriculum in the foundations of biomedical informatics while fostering your specialized skills in one of our field’s five key areas: 11/17/16 Bioinformatics 11/17/16 Biomedical Ontology 9/28/23 Clinical Informatics 11/17/16 Public Health Informatics 11/17/16 Sociotechnical and Human-Centered Design As a PhD candidate, you’ll take upper-level classes in your specialty area. You’ll conduct your research with a dedicated faculty member who has the type of expertise and research portfolio you wish to develop — a dedicated mentor who will guide you through every phase of your research. The result of this tailored approach to your training? You’ll graduate from our program ideally positioned for a career at the leading edge of biomedical informatics. Access Sophisticated Resources Harness the data you need for your research. Stay abreast of the latest work in our field. Train with this region’s leading experts and most advanced tools. Our PhD candidates enjoy an all-access pass to UB’s state-of-the-art computational resources as well as the sophisticated initiatives led by our campus and regional partners. Among others, these resources include: the Institute for Healthcare Informatics , a 3+HIPAA-compliant data storage and computing facility the UB Center for Computational Research , one of the leading academic supercomputing sites in the U.S. UB’s Clinical and Translational Science Institute, the regional hub of translational research  UB’s Virtual Computing Lab, which features MATLAB, Minitab, SPSS and other research software tools the Ontology Research Group , a nationally recognized center for ontology and electronic health records the Population Health Observatory , a research, training and data center in the School of Public Health and Health Professions the Upstate N.Y. Practice-Based Research Network , a center for outcomes research HEALTHeLINK , a health information exchange the Health Sciences Library , which conducts a variety of training programs in bioinformatics Co-Director, PhD Degree Program Werner Ceusters, MD Division Chief, Biomedical Ontology Department of Biomedical Informatics 77 Goodell street Buffalo, NY 14203 Phone: (716) 881-8971 Email: [email protected] Open positions Research Staff Alumni & Collaborations Software packages Current Assembly Projects Older Assembly Projects Metagenomic Databases Ph.D. Programs JHU courses Summer Internships Consulting Core Information for prospective Ph.D. students in Computational Biology or Bioinformatics The Ph.D. programs in Computational Biology at Johns Hopkins University span four Departments and a wide range of research topics. Our programs provide interdisciplinary training in computational and quantitative approaches to scientific problems that include questions in genomics, medicine, genome engineering, sequencing technology, molecular biology, genetics, and others. Our students are actively involved in high-profile research, and have developed very widely-used bioinformatics software systems such as Bowtie , Tophat , and Cufflinks . and the more-recent systems HISAT and Stringtie (for RNA-seq alignment and assembly) and Kraken (for metagenomic sequence analysis). The work they do with Hopkins faculty prepares them to go on to postdoctoral and tenure track faculty positions at top-ranked universities including (in recent years) Harvard, the University of Washington, Carnegie Mellon, the University of Maryland, and Brown. Students in computational biology at Hopkins can enroll in one of four different Ph.D. programs. These include Biomedical Engineering, ranked #1 in the nation; Biostatistics, also ranked #1 in the nation; Biology, ranked #6 in the nation; and the rapidly growing Computer Science Department, ranked #23 in the nation. Hopkins is also ranked #4 in the nation in Bioinformatics, a ranking that just started appearing in 2022. CCB faculty have appointments in each of these programs, and some of us maintain appointments in multiple programs. To determine which program fits your interests and background, browse the course lists below. Each program has a separate application process; please apply specifically to the departments you're interested in. Applications to multiple programs are permitted, but if you're not certain, we encourage you to contact potential faculty advisors before you apply. Wherever you apply, make it clear that your interest is Computational Biology. Sample Course Offerings for Ph.D. students in Computational Biology Department of biomedical engineering, whiting school of engineering. The Johns Hopkins Department of Biomedical Engineering (BME), widely regarded as the top program of its kind in the world and ranked #1 in the nation by U.S. News , is dedicated to solving important scientific problems at the intersection of multiple disciplines and that have the potential to make a significant impact on medicine and health. At the intersection of inquiry and discovery, the department integrates biology, medicine, and engineering and draws upon the considerable strengths and talents of the Johns Hopkins Schools of Engineering and Medicine. See the BME Ph.D. program website for many details. Department of Computer Science, Whiting School of Engineering The faculty represent a broad spectrum of disciplines encompassing core computer science and many cross-disciplinary areas including Computational Biology and Medicine, Information Security, Machine Learning, Data Intensive Computing, Computer-Integrated Surgery, and Natural Language Processing. Ph.D. program A total of 8 courses are required, and a typical load is 3 courses per semester. See the CS Department website for details. For a look at courses that might be included in Ph.D. training, see this page , though note that it is not a comprehensive list. For the Computer Science Ph.D., 2 out of the required 8 classes can be taken outside the Department. These may include any of the courses in the BME, Biostatistics, and Biology programs listed on this page. Department of Biostatistics, Bloomberg School of Public Health Johns Hopkins Biostatistics is the oldest department of its kind in the world and has long been considered as one of the best. In 2022, it was ranked #1 in the nation by U.S. News . All students in the Biostatistics Ph.D. program have to complete the core requirements: A two-year sequence on biostatistical methodology (140.751-756) A two-year sequence on probability and the foundations and theory of statistical science (550.620-621, 140.673-674, 140.771-772); Principles of Epidemiology (340.601) In addition, students in computational biology might take: 140.776.01 Statistical Computing (3 credits) 140.638.01 Analysis of Biological Sequences (3 credits) 140.644.01 Statistica machine learning: methods, theory, and applications (4 credits) 140.688.01 Statistics for Genomics (3 credits) Further courses might include 2-3 courses in Computer Science, BME, or Biology listed on this page. Department of Biology, Krieger School of Arts and Sciences The Hopkins Biology Graduate Program, founded in 1876, is the oldest Biology graduate school in the country. People like Thomas Morgan, E. B. Wilson, Edwin Conklin and Ross Harrison, were part of the initial graduate classes when the program was first founded. Hopkins is ranked #6 in the nation in Biological Sciences by U.S. News Quantitative and computational biology are an integral part of the CMDB training program. During the first semester students attend Quantitative Biology Bootcamp, a one week intensive course in using computational tools and programming for biological data analysis. Two of our core courses - Graduate Biophysical Chemistry and Genomes and Development - each have an associated computational lab component. Ph.D. in Cell, Molecular, Developmental Biology, and Biophysics (CMDB): The CMDB core includes the following courses: 020.607 Quantitative Biology Bootcamp 020.674 Graduate Biophysical Chemistry 020.686 Advanced Cell Biology 020.637 Genomes and Development 020.668 Advanced Molecular Biology 020.606 Molecular Evolution 020.620 Stem Cells 020.630 Human Genetics 020.640 Epigenetics & Chromosome Dynamics 020.650 Eukaryotic Molecular Biology 020.644 RNA Students in computational biology can use their electives to take more computationally intensive courses. You have considerable flexibility to design a program of study with your Ph.D. advisor. The Center for Computational Biology at Johns Hopkins University University Catalog 2024-2025 Bioinformatics (phd). Degree Requirements Course List Code Title Hours Counts towards Genomics Sciences Core Courses 12 Special Topics (Bioinformatics I) Functional Genomics Special Topics (Genomic Sciences Journal Club) Molecular Genetics Macromolecular Synthesis and Regulation Professionalism and Ethics Bioinformatics Core Courses 12 Special Topics (Bioinformatics II) Computational Methods for Molecular Biology Statistical Methods For Researchers II Advanced Topics in Statistics (Bioinformatics Consulting) Bioinformatics PhD Courses 8 Special Topics (Genomic Sciences Journal Club) Fundamentals of Statistical Inference I Fundamentals of Statistical Inference II Elective Courses 9 "Elective Courses" will be determined in conjunction with the academic committee Doctoral Research Courses 32 "Doctoral Research Courses" will be determined in conjunction with the academic committee Total Hours 73 PP 810  Genomic Sciences Journal Club should be repeated four times (twice for "Genomic Sciences Core Courses" and twice for "Bioinformatics PhD Courses"). Full Professors Jose Miguel Alonso Christopher M. Ashwell Russell J. Borski Matthew Breen Dennis T. Brown Ignazio Carbone Marie Davidian Robert Graham Franks Sujit K. Ghosh Amy Michele Grunden Jason M. Haugh Erich L. Kaltofen Robert M. Kelly Matthew D. Koci Cristina Lanzas Hsiao-Ching Liu Christian Maltecca Earl S. Maxwell Melissa Schuster Merrill David C. Muddiman Spencer V. Muse Charles H. Opperman James N. Petitte Robert M. Petters Jorge A. Piedrahita Brian J. Reich Maria C. Sagui Seth M. Sullivant Jung-Ying Tzeng Mladen Alan Vouk Ross W. Whetten Fred Andrew Wright Qiuyun Xiang Zhaobang Zeng Daowen Zhang Associate Professors David Lawrence Aylor Nicolas Buchler Gavin Clay Conant Michael B. Goshe Steffen Heber Slavko Komarnytsky David S. Lalush Terri A. Long Arnab Maity Flora Meilleur Dahlia M. Nielsen Jonathan W. Olson Xinxia Peng David Michael Reif Michael L. Sikes Charles Eugene Smith Lori June Unruh Snyder Assistant Professors Orlando Arguello-Miranda Hamid Ashrafi Christa Baker Louis-Marie Bobay Benjamin J. Callahan Abdulkerim Eroglu Rafael Felipe Guerrero Farias Denis Fourches Joseph Lee Gage Caitlin Heil Amanda Marie Hulse Jicai Jiang Xingcheng Lin Kurt Marsden David Rasmussen Christina Zakas Emeritus Faculty William Reid Atchley Wendy F. Boss Rebecca S. Boston James W. Brown Vincent L. C. Chiang Eugene Eisen Todd Robert Klaenhammer Jeffrey Thorne Wayne Tompkins Anastasios A. Tsiatis Paul L. Wollenzien Print Options Send Page to Printer Print this page. Download Page (PDF) The PDF will include all information unique to this page. 2024-2025 Undergraduate Catalog A PDF of the entire 2024-2025 Undergraduate catalog. 2024-2025 Graduate Catalog A PDF of the entire 2024-2025 Graduate catalog. 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The best PhDs in Bioinformatics degree programs at top private and public universities can help you become a leading professional in the field. If you’re wondering how to begin pursuing a bioinformatics PhD, this guide will cover 10 of the best academic programs available, as well as the funding opportunities and admissions process of each. We’ll also explore exciting bioinformatics jobs and the top PhD in Bioinformatics salary opportunities that await graduates. Find your bootcamp match What is a phd in bioinformatics. A PhD, or Doctor of Philosophy in Bioinformatics refers to an interdisciplinary, post-graduate program that integrates the real-world experience of research and applying computer technology to the analysis and management of biological data. PhD in Bioinformatics degrees teach students to organize data from multiple experiment databases, create new algorithms, and use software and mathematical modeling to interpret biological information. Advanced bioinformatics PhD students gain the knowledge, computational skills, and scientific skills necessary to apply the latest technology to biological data. In addition, they leverage different techniques to find solutions to diseases. How to Get Into a Bioinformatics PhD Program: Admission Requirements The admission requirements for a PhD in Bioinformatics program include a 3.0 GPA, letters of recommendation, a personal statement, a current resume, official transcripts, and a master’s degree in a relevant field. Some universities will require GRE exam scores and approval by the department. Certain universities will accept students with a bachelor’s degree in a relevant field. All international and English as a second language-speaking (ESL) students will need to submit proof of English proficiency in the form of the Test of English as a Foreign Language (TOEFL) exam scores or an equivalent proficiency exam. Admission processes will vary by school, so you should carefully examine the school’s requirements before submitting your application. PhD in Bioinformatics Admission Requirements 3.0 minimum GPA Letters of recommendation Relevant master’s or bachelor’s degree Official transcripts GRE exam scores, depending on school Updated resume TOEFL exam or equivalent for international and ESL students Bioinformatics PhD Acceptance Rates: How Hard Is It to Get Into a PhD Program in Bioinformatics? It can be very hard to get into a PhD program in Bioinformatics because it is a highly specialized field that often requires real-world experience. Depending on the university you apply to, you will encounter different acceptance rates. You can learn how competitive the program is by searching for acceptance or admission rates on the program’s website. Nevertheless, if you’re an outstanding student who achieved exceptional grades in a relevant master’s or bachelor’s program, you can be sure it will be easy to find an opportunity for acceptance in most universities. How to Get Into the Best Universities [query_class_embed] how-to-get-into-*school Best PhDs in Bioinformatics: In Brief School Program Online Option Colorado State University PhD in Biological Science No Columbia University PhD in Biomedical Informatics No Cornell University PhD in Computational Biology No Johns Hopkins University PhD in Pathobiology No Northern Arizona University PhD in Informatics and Computing No University of Arizona PhD in Biostatistics No University of California, LA PhD in Bioinformatics No University of Illinois, Chicago PhD in Bioinformatics No University of Miami PhD in Biomedical Engineering No The University of Utah PhD in Molecular Biology No Best Universities for Bioinformatics PhDs: Where to Get a PhD in Bioinformatics The best universities for bioinformatics PhDs include the University of Utah, John Hopkins University, the University of California, Cornell University, Columbia University, and the University of Miami. If you’re looking for a top university with graduate bioinformatics degree programs, read below for details on each of the best programs available. Colorado State University is a public academic institution founded in 1870. Located just under two hours from Denver, CSU has eight colleges that provide numerous graduate programs to over 3,500 graduate and doctoral students.  PhD in Biological Science Students of this biological science program will learn basic and applied biological research and have the choice of specializing in bioinformatics. To complete this 72-credit program, you will need the BZ 779 Dissertation, which has a minimum of 32 credits. Prospective students should contact the department advising faculty to match with an advisor for successful admission.  PhD in Biological Science Overview Program Length : 5 years Acceptance Rate : N/A Tuition and Fees : $601.90/credit (in state); $1,475.80/credit (out of state) PhD Funding Opportunities : Graduate assistantships, Marshall and Rhodes grants, and the Martin Luther King, Jr. Graduate Scholarship PhD in Biological Science Admission Requirements Master's or bachelor’s degree in a relevant field Three letters of recommendation Statement of purpose Approval by the admission board Founded in 1754 by King George II, Columbia University was initially known as King's College. It is the oldest higher learning institute in New York and the fifth oldest in the US. The private university offers numerous PhD programs , including programs in art history, astronomy, chemical physics, and biological sciences. PhD in Biomedical Informatics Columbia University's bioinformatics PhD program concentrates on courses such as clinical informatics, bioinformatics, public health informatics, and clinical research informatics. The degree requirements include 60 credit units in coursework, two specialization courses, an ethics unit, a research seminar, and two classes of teaching assistant work.  Acceptance Rate : 5 - 7% Tuition and Fees : $25,248/semester PhD Funding Opportunities : Graduate assistantships, fellowships, and National Library of Medicine funding GRE exam scores Bachelor's or master’s degree in a relevant field Writing supplement Personal statement Cornell University is a private research university founded in 1865 by Ezra Cornell and Andrew Dickinson White. Cornell offers numerous fully-funded PhD degrees, including programs in management, animal science, applied mathematics, molecular and cell biology, and astronomy and space sciences. PhD in Computational Biology This PhD in Computational Biology program blends mathematics, technology, and biology to train students to produce computational models of biological and genomic data. Students of this interdisciplinary program are taught and advised by faculty from 16 different fields and explore topics such as neuroscience, protein structure and databases, and biomechanics.  PhD in Computational Biology Overview Program Length : 5 - 6 years Acceptance Rate : 5 - 10% Tuition and Fees : $20,800/year PhD Funding Opportunities : Graduate assistantships, research assistantships, and fellowships PhD in Computational Biology Admission Requirements Official transcripts  Master’s degree Two to three letters of recommendation GRE exam scores (optional but encouraged) Application fee John Hopkins University is a private research university named after its initial benefactor, John Hopkins. Founded in 1876, it was the first research university to be established in the United States. Some of the most renowned and highly-ranked doctoral programs at John Hopkins include medicine, biological sciences, biostatistics, and public health.   PhD in Pathobiology This PhD in Pathobiology program provides an active learning, evidence-based approach to pathobiology. Enrolled students are fully funded, with average costs of over $98,000 per student covered by the university. At the end of the program, students will be prepared for academic, teaching, research, and biotechnology positions to find solutions to various diseases. PhD in Pathobiology Overview Program Length : 5.5 years Acceptance Rate : 9% Tuition and Fees : No fees PhD Funding Opportunities : Fully funded by Johns Hopkins with a $34,910 yearly stipend PhD in Pathobiology Admission Requirements Current resume Bachelor’s or master’s degree GRE scores (optional) Northern Arizona University is a public research university founded in 1899. NAU offers over 100 doctoral programs and enrolls over 4,500 graduate students. The school is ranked 57th on the list of the most innovative schools in the United States by US News & World Report.  PhD in Informatics and Computing PhD students enrolled in this program have the choice of specializing in Bioengineering Informatics, Cyber and Software Systems, Ecological and Environmental Informatics, or Health and Bioinformatics. Degree requirements include research, preparing and defending a dissertation, comprehensive exams, and completing 60 to 109 credit units of graduate courses.  PhD in Informatics Overview Tuition and Fees : $12,250/year (in state); $28,240/year (out of state) PhD Funding Opportunities : CEIAS Scholarship, VMWare Scholarship, employee tuition reduction, and graduate assistantships and tuition waivers PhD in Informatics Admission Requirements Personal statement or essay Relevant expertise in informatics The University of Arizona is a public research university founded in 1885 by the Arizona Territorial Legislature. It was the first higher learning institution in the state. As a member of the Association of American Universities and the Universities Research Association, UA offers numerous top-quality doctoral degree programs. Top PhD programs include audiology, education, natural sciences, nursing, and musical arts. PhD in Biostatistics UA's biostatistics PhD program covers topics such as bioinstrumentation, molecular biophysics, interfacial biosystems engineering, polymeric science and engineering, and neural and neuromuscular prostheses. To get a PhD degree in this specialization, students must complete 74 credits of coursework, a dissertation, and qualifying examinations. PhD in Biostatistics Overview Program Length : 6 to 7 years Acceptance Rate : 81.82% Tuition : $13,400/year (in state); $33,600/year (out of state) PhD Funding Opportunities : Graduate scholarships and assistantships, Named scholarships, and the Western Regional Graduate Program PhD in Biostatistics Admission Requirements Master’s Degree in Statistics, Biostatistics, or a relevant field  3.2 minimum GPA Statement of purpose, writing sample, and a mission and values statement Documented experience in computer programming (C++, Java, Python, or R programming languages) highly recommended The University of California, Los Angeles (UCLA) was founded in 1882 as a teacher's college. Today, UCLA provides over 120 graduate programs to 6,000 newly admitted graduate students per year. Numerous graduate programs at UCLA are repeatedly ranked among the top programs in the world.  PhD in Bioinformatics Students in this program will enjoy research, training, and collaboration opportunities with some of the most expert faculty and professionals in the world of bioinformatics. Students have access to one of the largest computer grids in the US to explore topics like human genome evolution, population genetics, and computational methods to analyze epigenomic data.  Acceptance Rate : 28% Tuition and Fees : $17,756/year (in state); $32,858/year (out of state) PhD Funding Opportunities : Graduate assistantships, training grants, GEM Fellowship, UC HBCU Initiative, Dissertation Year Fellowship, and graduate student researcher positions Current Resume GRE exam scores (optional) The University of Ilinois at Chicago was established in 1965 and enrolls over 33,000 students. Located on the West Side of Chicago, UIC is Chicago’s only public research university and is recognized for its cultural diversity. UIC’s graduate school departments offer 61 different doctoral programs to students in a wide range of fields.  Core topics of this 108-credit program include machine learning, the principles of bioinformatics, and statistical mechanics in biological systems. Students of this program will complete and defend a dissertation, pass preliminary and qualifying exams, and complete at least two research seminars before graduation to obtain the PhD.  "Career Karma entered my life when I needed it most and quickly helped me match with a bootcamp. Two months after graduating, I found my dream job that aligned with my values and goals in life!" Venus, Software Engineer at Rockbot PhD in Bioinformatics Overview Program Length : N/A Tuition and Fees : $5,935/semester (in state); $12,369/semester (out of state) PhD Funding Opportunities : Teaching assistantships, research assistantships, tuition waivers, and fellowships Bachelor’s or Master’s Degree in Physics, Mathematics, Science, or a related field  Personal Statement The University of Miami is a private research university established in South Florida in 1925. The university enrolls over 17,000 students in over 12 schools and colleges. It is known for its extensive undergraduate and doctoral programs in marine science, psychology, education, engineering, and medicine.  PhD in Biomedical Engineering The University of Miami takes biomedical engineering PhD students through key topics such as neurophysiology, cellular and molecular biology, and anatomy. Students of this 60-credit program are required to complete and defend a dissertation, pass oral qualifying exams, and publish at least two pieces of research. Graduates will be prepared for careers in academic or independent research in biomedical engineering. PhD in Biomedical Engineering Overview Tuition and Fees : $19,917/semester PhD Funding Opportunities : UM Fellowship, Maytag Fellowship, and Dean’s Fellowship PhD in Biomedical Engineering Admission Requirements Master's Degree in Biomedical Engineering or highly qualified candidates with a bachelor’s degree in a related scientific field The University of Utah was founded in 1850 as the University of Deseret. It now hosts over 8,000 graduate students in more than 100 master’s and doctoral programs. The University of Utah has become a leader in the world of biomedical informatics since its program’s founding in 1964.  Students in this program will cover the fundamentals of informatics and explore core coursework topics including translational informatics, grant writing, healthcare informatics, and statistics for biomedicine. The program is fully funded by the university and students will have the option of specializing in an informatics field of choice.  PhD in Biomedical Informatics Overview Program Length : 3 to 4 years PhD Funding Opportunities : Program fully funded by the University of Utah with a $29,710 yearly stipend PhD in Biomedical Informatics Admission Requirements 3.0 Minimum GPA  Approval by the department administration standards Can You Get a PhD in Bioinformatics Online? Yes, you can get a PhD in Bioinformatics online. Since the research work is computational, you can obtain your doctoral degree remotely as long as you fulfill all of the graduation requirements. However, you may have to apply to universities or colleges outside of your state to access online bioinformatics PhD programs. Best Online PhD Programs in Bioinformatics School Program Length Bircham International University PhD in Bioinformatics 2 years George Mason University PhD in Bioinformatics and Computational Biology N/A Rutgers University PhD in Health Informatics 4 years How Long Does It Take to Get a PhD in Bioinformatics? Generally, it takes four to six years to complete a PhD in Bioinformatics. However, depending on the university and the specialization you pursue, you can spend three to five years completing the program. Certain programs will take more time than others, and online or part-time programs can often take longer to finish than full-time, on-campus programs. Is a PhD in Bioinformatics Hard? Yes, earning a PhD in Bioinformatics is hard. Students pursuing this degree must complete intensive coursework, exams, and other requirements such as a dissertation or thesis. Moreover, some departments will demand prior requirements such as computer programming and mathematical skills, which can be challenging to acquire. It takes a lot of effort to obtain a PhD in Bioinformatics. Nonetheless, the effort is worth it. With hard work and time, obtaining a bioinformatics PhD is feasible. How Much Does It Cost to Get a PhD in Bioinformatics? The average tuition for a bioinformatics PhD program is $19,315 per year across all higher education institutions, according to the National Center for Education Statistics. However, this value varies depending on the university. Some institutions will fund their bioinformatics PhD students completely, while others may ask for higher or lower tuition costs than the stated figures. Attending a private institution is often more expensive than a public institution, and it is best to research the costs and funding opportunities available for both. How to Pay for a PhD in Bioinformatics: PhD Funding Options The PhD funding options that students can take advantage of to pay for a PhD in Bioinformatics degree program include scholarships, graduate assistantships, fellowships, and tuition waivers. Some institutions, like the University of Utah and Johns Hopkins University, offer enrolled students fully-funded tuition, a yearly stipend, and health insurance. Best Online Master’s Degrees [query_class_embed] online-*subject-masters-degrees What Is the Difference Between a Bioinformatics Master’s Degree and PhD? The difference between a bioinformatics master’s degree and a PhD is the content of the curriculum and the number of years required to complete the program. While master’s degree programs typically take around two years, PhDs take an extended period of up to six or seven years. Bioinformatics master’s degrees will cover foundational concepts, but PhDs focus on advanced knowledge and specialized, applicable skills in the field. Additionally, PhDs offer superior job positions compared to master’s degrees because they are the highest form of educational qualification one can have in a particular field of study. Master’s vs PhD in Bioinformatics Job Outlook The employment rate for bioengineers, a profession that typically only requires a bachelor’s or master’s degree, is projected to grow by six percent in the next decade , according to the Bureau of Labor Statistics. This is much lower than the rate of employment growth for bioinformatics scientists, which is expected to increase by 22 percent . This shows that the demand for PhD degree candidates in the bioinformatics field is higher than that of master’s degree holders. Having a PhD in Bioinformatics makes you the most qualified candidate for most positions and you can be assured of securing numerous lucrative career opportunities. Difference in Salary for Bioinformatics Master’s vs PhD A PhD in Bioinformatics graduate earns an average base salary of $116,000 per year, according to PayScale. This does not include the numerous benefits and perks of this position. Moreover, some cities offer higher pay, such as San Francisco, San Diego, and New York. With a Master’s Degree in Bioinformatics, candidates earn an average annual salary of $83,000. A PhD in Bioinformatics graduate earns almost double the salary of a master’s degree holder. Related Bioinformatics Degrees [query_class_embed] https://careerkarma.com/blog/best-bioinformatics-bachelors-degrees/ https://careerkarma.com/blog/best-bioinformatics-masters-degrees/ https://careerkarma.com/blog/bioinformatics/ Why You Should Get a PhD in Bioinformatics You should get a PhD in Bioinformatics to enjoy the numerous benefits of this qualification. With a PhD, you will become a certified expert in the field. Below are some of top the reasons you should consider pursuing a bioinformatics PhD. Reasons for Getting a PhD in Bioinformatics Career development . A PhD in Bioinformatics is essential to secure senior positions in the field. This doctoral degree proves that you have the relevant knowledge and skills to handle top positions in renowned companies, and gives you an edge over the competition in the job market. Academic achievement . Aside from securing a dream job, some people feel most accomplished when achieving their academic goals. You can pursue a PhD in Bioinformatics to improve your skills and intensive knowledge in this scientific field. Innovative health projects . The best bioinformatics degree programs will equip you with new knowledge and skills in science, computing, and health. You can utilize these skills to work on groundbreaking projects, such as finding a biological solution or cure to a disease. Higher earning potential . A PhD automatically increases a degree holder’s earning potential, and can lead to salaries that are double what they would be with a bachelor’s or master’s degree. Getting a PhD in Bioinformatics: Bioinformatics PhD Coursework Getting a PhD in Bioinformatics requires candidates to complete core bioinformatics PhD coursework in mathematics, statistics, computing, and biology. Below are a few of the most common core courses you may see in a bioinformatics PhD program curriculum. Introduction to Bioinformatics This course introduces students to the fundamental concepts of bioinformatics. It teaches about the different tools and techniques used in the field and how they are applied. It is typically a combination of theory and practical skills and topics for students to gain hands-on experience applying bioinformatics tools and solutions. Bioinformatics Resources and Databases This course involves the study of biological databases, data formats, ontologies, and biological resources. This course helps you learn how to obtain and apply different databases to find solutions in the field. This course focuses on teaching students how to learn Linux , an operating system that is heavily utilized in the field of bioinformatics. It covers the introduction to Linux, Linux environment, command-line interface, manipulating files and directories, navigating Linux directory structure, and primary Linux commands. Multiple Sequence Alignment This course introduces students to multiple sequence alignment theory (MSA), and a protein, DNA, or RNA biological sequence alignment. Students will learn about visualization and assessment of MSA quality, and how to use proper tools for MSA analysis. Molecular Evolution and Phylogenetics A course in molecular evolution and phylogenetics focuses on how different species and genes are related. The course will cover introductory and overview methods of molecular evolution and phylogenetic approaches. Best Master’s Degrees [query_class_embed] *subject-masters-degrees How to Get a PhD in Bioinformatics: Doctoral Program Requirements When undertaking a PhD in Bioinformatics, you’ll have to fulfill all of the doctoral program requirements. Whether you are pursuing a PhD in Informatics and Computing, Information Science, or Pathobiology, below are the typical requirements you’ll need to fulfill to get your degree. A PhD in Bioinformatics program will state the total credit hours you’ll have to complete to obtain your doctoral degree, as well as any required publication or research work. Programs can have credit requirements from 65 to over 100 credit hours. Many graduate assistantships or fully-funded programs will require students to publish articles in peer-reviewed journals or assist faculty in research. Like many other degrees, PhD in Bioinformatics programs require multiple comprehension and qualifying exams for students to test whether they've mastered different key concepts in the field. To receive your Doctor of Philosophy degree, you must pass the preliminary and qualifying exams.  As a highly-qualifying program of study, the best universities offering PhD in Bioinformatics degrees usually require a minimum GPA that candidates must maintain. Some programs will not allow candidates to graduate or will suspend funding or assistantships if a certain GPA is not met throughout their studies.  Each bioinformatic PhD program entails certain coursework that students must complete in order to be certified in a specific area. This coursework is typically divided into different units in the curriculum, such as core courses, research and dissertation hours, and elective courses.  Before enrolling in any PhD program, you should research the course curriculum in the school catalog to ensure that the curriculum is a good fit for your interests and career goals.  Perhaps the most vital requirement for a bioinformatics PhD is the thesis or dissertation. A dissertation is a research project where students answer a particular question or solve a problem that is relevant to their field of study.  The dissertation usually has to be orally defended in front of the department, and this allows the faculty to evaluate whether the candidate has acquired the necessary research skills to enable them to find a solution to real-world problems and situations.  Potential Careers With a Bioinformatics Degree [query_class_embed] how-to-become-a-*profession PhD in Bioinformatics Salary and Job Outlook A PhD in Bioinformatics degree increases your qualifications for employment and your earning potential significantly. The job outlook for PhD holders in this field is 22 percent more than the national average for all other occupations. Therefore, you can always find a viable career opportunity in the field, from teaching in a university to industry research. What Can You Do With a PhD in Bioinformatics? With a PhD in Bioinformatics, you can join leading experts in many different career paths. You can also enjoy top-paying job opportunities with numerous benefits and exclusive perks to boost your productivity, job satisfaction, and career development. Below are some of the best bioinformatics jobs available to graduates. Best Jobs with a PhD in Bioinformatics Computer and Information Research Scientist Postsecondary Teacher Bioinformatician Senior Research Scientist Principal Investigator/Clinical Research What Is the Average Salary for a PhD in Bioinformatics? The average PhD in Bioinformatics salary is $116,000 per year , according to PayScale. This value can vary depending on your location and the company you work for. Check out some of the best high-paying bioinformatics jobs below. Highest-Paying Bioinformatics Jobs for PhD Grads Bioinformatics PhD Jobs Average Salary Computer and Information Research Scientist Principal Scientist Senior Research Scientist in Biotechnology Bioengineer or Biomedical Engineer Principle Investigator in Clinical Research Best Bioinformatics Jobs with a Doctorate The job opportunities for candidates with a PhD in Bioinformatics are endless. Below you’ll find information regarding job duties, job outlook, and annual salary information for some of the best jobs available in the field of bioinformatics. Computer and information research scientists use their analytical and statistics skills to identify and improve computing problems in a wide range of industries. Job duties of these professionals can include working with scientists to identify and solve a technological problem and utilizing machine learning and data science concepts to conduct experiments and tests.  Salary with a Bioinformatics PhD : $131,490 Job Outlook : 22% job growth from 2020 to 2030 Number of Jobs : 33,000 Highest-Paying States : Oregon, Arizona, and Texas Principal or head scientists often lead teams of qualified research professionals that collect data on different phenomenons, from genetic sequencing to hereditary diseases. Their expertise and dedication to science allow them to properly analyze and predict trends, and they generally focus on advancing the scientific field itself as opposed to the profits of an industry.  Salary with a Bioinformatics PhD : $125,801 Job Outlook : 17% job growth from 2020 to 2030 Number of Jobs : 133,900 Highest-Paying States : Connecticut, Maine, and Delaware Senior research scientists in biotechnology engage in biology, mathematics, computer science, and/or chemistry research operations for companies, organizations, or universities. They often focus on academic and industrial projects to create new products or systems and conduct experiments to analyze developments in the field.  Salary with a Bioinformatics PhD : $108,465 Bioengineers work with computing and data science, engineering, and human health. These professionals typically work in research to develop new statistical models, software, or even drugs and cures to diseases, or quality assurance to test and inspect computer systems, equipment, and processes to ensure safety and effectiveness.  Salary with a Bioinformatics PhD : $97,410 Job Outlook : 6% job growth from 2020 to 2030 Number of Jobs : 19,300 Highest-Paying States : New Mexico, Arizona, and Minnesota Principle investigators in clinical research often work in laboratories and lead a team of scientists to conduct clinical research and tests regarding different diseases or medical phenomena. Objectives vary by field, but the principal investigator is in charge of assisting and offering guidance to team members and offering expertise in the research process.  Salary with a Bioinformatics PhD : $85,000 Is a PhD in Bioinformatics Worth It? Yes, a PhD in Bioinformatics is worth it. With this doctoral qualification, you will stand out from other candidates, as a PhD degree proves that you have specialized, expert knowledge and skills to perform any role in bioinformatics exceptionally. With a high-earning potential in a growing field, pursuing a PhD in Bioinformatics will prove to be more than worth it. Additional Reading About Bioinformatics [query_class_embed] https://careerkarma.com/blog/python-for-bioinformatics/ https://careerkarma.com/blog/bachelor-of-science-biology/ https://careerkarma.com/blog/biotech-companies/ PhD in Bioinformatics FAQ Yes, you can get a top-quality PhD in Bioinformatics online at schools like Bircham International University, Rutgers University, and George Mason University. These institutions allow you to pursue your Doctor of Philosophy in Bioinformatics remotely and at your own pace. The most affordable PhD in Bioinformatics programs are those that are fully funded by the university. These programs include the PhD in Pathobiology offered by Johns Hopkins and the PhD in Biomedical Informatics program at the University of Utah. These two universities cover the full tuition amount and even provide students with a yearly stipend to cater to other needs. No, you typically cannot get an application fee back after you withdraw your application. Most application fees are non-refundable because they facilitate the entire evaluation process and prove to the department that you are serious about attending the program. No, a Master’s Degree in Bioinformatics is not always a mandatory admission requirement. Many universities will accept candidates for bioinformatics PhD programs as long as they have a master’s degree in a relevant course, and other universities will accept highly qualified candidates with only a bachelor’s degree. About us: Career Karma is a platform designed to help job seekers find, research, and connect with job training programs to advance their careers. Learn about the CK publication . What's Next? Get matched with top bootcamps Ask a question to our community, take our careers quiz. Leave a Reply Cancel reply Your email address will not be published. Required fields are marked * 472 IMAGES Biochemistry & Bioinformatics: Dissertation Rewriting PPT PhD in Bioinformatics: PhD Admission bioinformatics thesis topics PPT PPT COMMENTS PhD Program The Department of Biomedical Informatics offers a PhD in Biomedical Informatics in the areas of Artificial Intelligence in Medicine (AIM) and Bioinformatics and Integrative Genomics (BIG).. The AIM PhD track prepares the next generation of leaders at the intersection of artificial intelligence and medicine. The program's mission is to train exceptional computational students, harnessing ... Current Research Topics in Bioinformatics A recent study has found that the interest of researchers in these topics plateaued over after the early 2000s [1]. Besides the above mentioned hot topics, the following topics are considered demanding in bioinformatics. Cloud computing, big data, Hadoop. Machine learning. Artificial intelligence. Bioinformatics PhD PhD in Bioinformatics and Systems Biology with emphasis in Biomedical Informatics. ... Topics covered include structuring of data, computing with phenotypes, integration of molecular, image and other non-traditional data types into electronic medical records, clinical decision support systems, biomedical ontologies, data and communication ... Computational Biology PhD This includes courses covering topics in molecular biology, genetics, evolution, environmental science, experimental methods, and human health. ... Computational Biology PhD students are required to teach at least two semesters (starting with Fall 2019 class), but may teach more. ... such as computational biology or bioinformatics; a major in a ... Bioinformatics and Integrative Genomics (BIG) PhD Track at HMS DBMI Email Cathy Haskell. 617-432-7856. PhD Program. Overview The Bioinformatics and Integrative Genomics (BIG) PhD track is an interdisciplinary program that trains future leaders in the field of bioinformatics and genomics. Our mission is to provide our graduate students with the tools to conduct original research in the development of novel ... PhD Program: Bioinformatics In 2023, the Bioinformatics Graduate Program maintains a student body of 87 PhD students, and over 120 Master's students. They are mentored by the 44 DCMB faculty and the 130 CCMB faculty. Faculty members with biological and more quantitative expertise are both well represented. The Bioinformatics Graduate Program was created in 1999 and is ... Computational and Systems Biology PhD Program The CSB PhD Program. ... Applicants must have an undergraduate degree in biology (or a related field), bioinformatics, chemistry, computer science, mathematics, statistics, physics, or an engineering discipline, with dual-emphasis degrees encouraged. ... Topics in Computational and Systems Biology (One Subject): ... Ph.D. in Computational Biology and Bioinformatics Program Description. The mission of the Graduate Program in Computational Biology and Bioinformatics (CBB) is to train predoctoral students to become leaders at the interdisciplinary intersection of quantitative and biomedical sciences. Genomics & Bioinformatics PhD Program The PhD in Genomics & Bioinformatics begins with interdisciplinary coursework in molecular, cellular, and systems biology in the first semester. In the second and third semester students take a comprehensive introduction to the conceptual and experimental underpinnings of computational biology, statistics, genetics, and DNA sequencing. ... Bioinformatics PhD Projects A Bioinformatics PhD would provide you with the opportunity to work on an extended, in-detail project through the analysis of large sets of data. Bioinformatics programmes tend to be mostly 'dry' work with limited (if any) time in the laboratory conducting experiments. Since the focus is analysis of data, the choice of projects spans many ... Bioinformatics Related Research Topics Our Research Focus. Today's data sets are of such magnitude and complexity that advanced bioinformatics methods are essential to their integration, management and dissemination. Our bioinformatics work incorporates data from both mouse and human genetic and genomic research and provides the annotations and interfaces necessary for delivering ... PhD in Bioinformatics Data Science PhD in Bioinformatics Data Science. A Ph.D. in Bioinformatics Data Science will train the next-generation of researchers and professionals who will play a key role in multi- and interdisciplinary teams, bridging life sciences and computational sciences. Students will receive training in experimental, computational and mathematical disciplines ... PhD in Biomedical Informatics PhD in Biomedical Informatics The PhD program in Biomedical Informatics is part of the Coordinated Doctoral Programs in Biomedical Sciences. Students are trained to employ a scientific approach to information in health care and biomedicine. Students may only enroll full-time, as required by the Graduate School of Arts and Sciences (GSAS). The first two years are Computational Biology and Bioinformatics (PhD) Students in the Computational Biology and Bioinformatics PhD program take graduate courses that cover topics from biology, computer science, mathematics, statistics and other disciplines. These courses guarantee a broad foundation in our field, and ensure students have sufficient scientific background and intellectual tools for success in research. Computational Biology & Biomedical Informatics (PhD Program) Computational biology and bioinformatics (CB&B) is a rapidly developing multidisciplinary field. The systematic acquisition of data made possible by genomics and proteomics technologies has created a tremendous gap between available data and their biological interpretation. Given the rate of data generation, it is well recognized that this gap will not be closed with direct individual ... PhD Program in Biomedical Informatics A PhD in biomedical informatics from UB prepares you to lead these organizations through complex information management challenges. With your advanced knowledge and skills, you'll apply sophisticated tools and methods to help design new systems and applications. Best of all, thanks to our close partnerships with regional health care ... Ph.D. programs in Computational Biology at JHU Information for prospective Ph.D. students in Computational Biology or Bioinformatics Note: every year, many students send applications directly to faculty members, but faculty members cannot accept students directly in any of our programs at Hopkins. You must apply to the Ph.D. programs through the Department websites given below. Harvard Medical School Bioinformatics and Integrative Genomics The Bioinformatics and Integrative Genomics PhD track led by Program Director Dr. Peter Park and Associate Director Dr. Maha Farhat, provides students with the tools to conduct original research and the ability to develop novel approaches and new technologies to address fundamental biomedical questions. The track draws on three significant ... Bioinformatics (PhD) < North Carolina State University Special Topics (Bioinformatics II) CSC 530. Computational Methods for Molecular Biology: ST 512. Statistical Methods For Researchers II : ST 810. Advanced Topics in Statistics (Bioinformatics Consulting) Bioinformatics PhD Courses: 8: PP 810. Special Topics (Genomic Sciences Journal Club) 1: ST 501. Fundamentals of Statistical Inference I: ST 502. Research Areas · PhD Degree Program in Biological and Medical Faculty members working in these areas include: 2. Genetics and genomics. Genetics is the study of DNA-based inheritance and variation of individuals, while genomics is the study of the structure and function of the genome. Both apply biological and medical informatics and computational techniques using data generated from methods such as DNA ... Best PhDs in Bioinformatics The PhD funding options that students can take advantage of to pay for a PhD in Bioinformatics degree program include scholarships, graduate assistantships, fellowships, and tuition waivers. Some institutions, like the University of Utah and Johns Hopkins University, offer enrolled students fully-funded tuition, a yearly stipend, and health ... Harvard PhD Program in Bioinformatics and Integrative Genomics Mission Statement. The interdepartmental Bioinformatics and Integrative Genomics (BIG) PhD program trains future leaders in the field of bioinformatics and genomics. Our mission is to provide BIG graduate students with the tools to conduct original research and the ability to develop novel approaches and new technologies to address fundamental biological questions. Frontiers in Bioinformatics An innovative journal that provides a forum for new discoveries in bioinformatics. It focuses on how new tools and applications can bring insights to specific biological problems. ... Research Topics. Submission open The Application of Multi-omics Analysis in Translational Medicine. HaiHui Huang; Madhu Chetty; 304 views Submission open assignment essay homework paper phd report resume review speech thesis