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.
The Team at Bioinformatics Review includes top notch bioinformaticians and scientists from across the world. Visit our Team page to know more.
You may like
You must be logged in to post a comment Login
You must be logged in to post a comment.
CMake installation and upgrade: What worked & what didn’t?!
CMake is a widely used cross-platform build system that automates the process of compiling and linking software projects. In bioinformatics, CMake can be utilized to manage the build process of software tools and pipelines used for data analysis, algorithm implementation, and other computational tasks. However, managing the versions of CMake or upgrading it on Ubuntu (Linux) can be a trivial task for beginners. In this article, we provide methods for installing and upgrading CMake on Ubuntu.
(more…)
Common mistakes made during computational docking.
Computational docking is not a trivial task once we avoid making some mistakes. In this section, let’s learn about some important points that we should keep in mind while performing computational docking.
How to download FASTA sequences from PDB for multiple structures?
In this article, we are going to download FASTA sequences for multiple structures from PDB [1]. We need to have PDB IDs only for input. (more…)
How to install the LigAlign plugin on Pymol on Ubuntu (Linux)?
Few errors appear when we try to run the LigAlign plugin [1] in Pymol [2]. For example, if you try to run the ligand_alignment plugin, it will give you multiple errors including “ Unable to initialize LigAlign v1.00 “, or “ can’t run LigAlign v1.00 ” or “ incorrect Python syntax ” or “ Plugin has been installed but initialization failed “. In this article, we explain the reason for this issue and how you can rectify these errors. (more…)
How to make an impactful science presentation?
After your hard work, it is time to showcase your study and the methods of your study to an audience. You must make every point useful and informative. Here, in this article, we are going to share some tips to make your scientific presentation impactful. (more…)
Basic bioinformatics concepts to learn for beginners
This article is for beginners who are stepping into the field of bioinformatics. We will discuss some basic concepts that you need to learn while trying to enter the field of bioinformatics. (more…)
A Beginner’s Guide on How to Write Good Manuscripts
Drafting a manuscript could be a difficult task for beginners in the field of research. In this article, we will provide a few tips for how can you write a good manuscript being a research scholar. (more…)
How to remove HETATMS and chains from PDB file?
This is a basic tutorial on removing the hetero-atoms (HETATMS) and chains from PDB files. It is an essential step for computational and molecular dynamics simulation. (more…)
Importance of Reasoning in Research
Research is considered complicated. As it involves reading multiple research articles and reviews, devising hypotheses and appropriate experiments, and last but not the least, getting a significant output. This seems difficult to read multiple research papers and then extract useful information regarding your project. It involves a methodology to read and understand research articles in one go. This is explained in our previous article “A guide on how to read the research articles” . This article explains the importance of thinking during your entire research. (more…)
How to Find Binding Pocket/ Binding Site for Docking?
Finding binding sites/pockets in a target protein is one of the important steps in docking studies. It is relatively easier to find a binding pocket in the proteins whose resolved structures are available in PDB than that of the predicted structures. In this article, we will discuss the ways to know a binding pocket or a binding site in a target protein. (more…)
Bioinformatics is an interesting field of research combining biological sciences and computer sciences. In this article, we will discuss making careers in bioinformatics for starters. (more…)
MD Simulation
Molecular dynamics (MD) simulation is considered amongst the important methods in bioinformatics. Installation of MD simulation software and execution of their commands is critical. It requires several parameters to be considered before performing simulations. A single mistake may result in impractical outputs. In this article, we will discuss such important things to remember during the MD simulation and installation and execution of its software (GROMACS) [1,2]. (more…)
Bioinformatics Books
It is difficult to decide which book to read to start learning bioinformatics. Beginners can read this article to know the basic steps involved in learning bioinformatics. A few books are suggested in this article to read for starters in bioinformatics. (more…)
Bioinformatics- Where & How to Start?
Bioinformatics being an interdisciplinary area of biological science and computer science may sound complicated to beginners in this field. However, it is quite simple. The only thing you need is knowledge in both areas. Here is a way for the beginners to start with bioinformatics. (more…)
Common mistakes made during Autodock Vina Installation and Execution
Several errors occur while installing MGLTools and Autodock Vina on Ubuntu. We have explained the complete process of Autodock Vina installation and docking in previous articles. Here are some common errors and mistakes that should be taken care of while installing and running Vina on Ubuntu. (more…)
What does a bioinformatician do?
Bioinformaticians play an important part in data analysis and result interpretation in the field of bioinformatics. However, it is unclear to many what specific role bioinformaticians play day to day. We are often asked by many about what exactly a bioinformatician does. But first, who is a bioinformatician?
MGL Tools & Autodock Vina installation: Frequently Asked Questions and Answers
I have received several e-mails from researchers and students alike regarding installing MGL Tools and Autodock Vina on Ubuntu. Most questions are similar in nature, so I thought of answering them once and for all. In this article, I have collected some frequently asked questions and provided the link to their answers in our question-answer section of Bioinformatics Review. (more…)
A guide on how to read the research articles
Reading a research article could be a problem for students starting their careers in research. Research papers are sometimes difficult to understand especially when you are new to this field. In this article, we will discuss how to read and understand a research article. (more…)
Bioinformatics and programming languages- what do you need to know!
There are various things which come to mind when someone is going to enter in the field of Bioinformatics and the topmost concern is “Do I need to learn computer languages to pursue my career in Bioinformatics?”. The answer is a bit tricky but it could be both “yes” and “no”. This article will describe the conditions where you need to learn programming languages in Bioinformatics. (more…)
Site-specific docking: Frequently Asked Questions & answers for starters
I have been getting several E-mails from researchers and students alike regarding in-silico docking. Most questions are similar in nature, so I thought of answering them once and for all. In this article, I have collected some frequently asked questions and provided the link to their answers present in our question-answer section of Bioinformatics Review.
It is good to have questions in mind and they can be solved in a way as quoted by Sir Einstein:
“We cannot solve our problems with the same thinking we used when we created them.”
In this article, I have collected some of the most Frequently Asked Questions while performing site-specific and/ or blind docking. You have to consider a lot of factors before performing an actual docking on a protein with a specific ligand.
Question: How do you predict protein’s binding sites?
Question: What is the difference between the blind docking and binding site based docking?
LATEST ISSUE
BSc and MSc Thesis Subjects of the Bioinformatics Group
On this page you can find an overview of the BSc and MSc thesis topics that are offered by our group. The procedure to find the right thesis project for you is described below.
MSc thesis: In the Bioinformatics group, we offer a wide range of MSc thesis projects, from applied bioinformatics to computational method development. Here is a list of available MSc thesis projects . Besides the fact that these topics can be pursued for a MSc thesis, they can also be pursued as part of a Research Practice .
BSc thesis: As a BSc student you will work as an apprentice alongside one of the PhD students or postdocs in the group. You will work on your own research project, closely guided by your supervisor. You will be expected to work with several tools and/or databases, be creative and potentially overcome technical challenges. Below you will find short descriptions of the research projects of our PhDs and Postdocs. In addition you can take a look at the list of MSc thesis projects above.
Procedure for WUR students:
- Request an intake meeting with one of our thesis coordinators by filling out the MSc intake form or BSc intake form and sending it to [email protected]
- Contact project supervisors to discuss specific projects that fit your background and interest
- Upon a match, take care of the required thesis administration together with your supervisor(s) and enroll in the thesis BrightSpace site to find more information on a thesis in the Bioinformatics group
Procedure for non-WUR students or students in other non-standard situations: We have limited space for interns from other institutes. If you are interested, please email our thesis coordinators at [email protected]; please attach your CV and indicate what are your main research interests.
BSc thesis topics
Integrative omics for the discovery of biosynthetic pathways in plants, molecular function prediction of natural products, linking the metabolome and genome, linking metagenomics and metatranscriptomics to study the endophytic root microbiome, exploiting variation in lettuce and its wild relatives.
Direct Links
JLU von A-Z
Informationen für
- Schülerinnen & Schüler
- Studieninteressierte
- Studierende
- Menschen mit Fluchthintergrund
- Unternehmen
- Jobs & Karriere
- Wissenschaftler/innen
- Promovierende
- Weiterbildungsangebote für JLU-Angehörige
- Lehrerfortbildung
- Wissenschaftliche Weiterbildung
- Ehemalige (Alumni)
- E-Campus ( Stud.IP , ILIAS , FlexNow , eVV )
Studium & Campus
- Vor dem Studium
- Studienangebot
- Bewerbung/Einschreibung
- Information/Beratung
- Vorlesungsverzeichnis
- Studien- und Prüfungsordnungen (MUG)
- Hochschulrechenzentrum
- Universitätsbibliothek
- Campusplan | Geschosspläne/JLUmaps
- Raumvergabe (ZLIS)
- Studierendenwerk/Mensen
- Corporate Design, Leitfäden, Logos
- Bildergalerie Pressestelle
- Formulare | Rundschreiben
- SAP & JustOS (JLU-Online-Shop)
- Rechtliche Grundlagen (MUG)
- Störungsmeldung
- Datenschutz
Karriere, Kultur, Sport, Marketing
- Allgemeiner Hochschulsport (ahs)
- Botanischer Garten
- Career Services
- Gender & JLU
- Hochschuldidaktik
- Justus' Kinderuni
- Sammlungen der JLU
- Universitätsorchester
- Uni-Shop/Merchandising
- E-Mail-Kontakt
- Telefonbuch
- Wegbeschreibung
- Call Justus
Open thesis topics
Within our group we can offer various topics in the field of applied bioinformatics, high-throughput data analysis, genome and metagenome research as well as postgenomics and systems biology. Below you can find a list of suggested open topics for BSc and MSc theses and student projects. For further details on each topic or alternative projects please contact us.
Exploring the Role of Nasal Microbiota in Neurological Diseases ( M.Sc.) Background Microorganisms, including those in the human nasal cavity, maintain stability and functionality. Recent research suggests a potential link between the nasal microbiota and neurological diseases such as Parkinson’s disease (PD), Alzheimer’s disease (AD), and multiple sclerosis (MS)(1). However, the nature of this relationship remains unclear due to a limited number of studies. While much focus has been on the gut-brain axis, the influence of the nose-brain axis on the immune system and respiratory homeostasis requires further investigation (2). Some studies have indicated that altering the nasal microbiota could potentially prevent or treat neurological diseases, highlighting the need to understand the complex interactions between the nasal microbiota and the brain. Evidence suggests that the nasal microbiome may travel through the olfactory pathway to the brain (2, 3). The diversity of bacteria in the nasal cavity is highly dynamic and can vary depending on age, physiology, and lifestyle. This project will investigate how nasal microbiota stability impacts the blood-brain barrier (BBB) and its potential role in the development and progression of neurological diseases. Our goal is to gain a comprehensive understanding of the nasal microbial community, the conditions under which it remains stable, and how disruptions in nasal homeostasis might contribute to neurodegeneration. Objective The primary objective of this project is to explore the conditions under which nasal microbiota stability or instability is associated with neurological diseases, focusing on potential diagnostic and therapeutic applications. Methodology 1. Literature Review: Conduct a thorough review of existing studies on the nasal microbiota and its potential impact on neurological diseases. 2. Data Comparison and Analysis: Compare data gathered from literature on the nasal microbiota, analyzing differences in composition and diversity, and identifying potential patterns. 3. Mechanistic Studies: Explore how alterations in the nasal microbiota might influence the BBB and contribute to the pathology of neurological diseases. 4. Model Creation and Analysis: Develop a model based on literature data to analyze the stability of the nasal microbiota and its potential role in modulating the risk of neurological diseases. Expected Outcome This project aims to shed light on the role of the nasal microbiota in neurological diseases, potentially leading to novel diagnostic and therapeutic strategies. By understanding the dynamics of nasal microbiota stability, we hope to uncover new insights into preventing and treating neurodegenerative conditions. Reference 1.García-Jiménez, Beatriz, et al., Computational and Structural Biotechnology Journal 19 (2021): 226-246. 2. Xie, Jin, et al. Pharmacological Research 179 (2022): 106189. 3. Thangaleela, Subramanian, et al., Microorganisms 10.7 (2022): 1405 Contact: Dr. Reihaneh Mostolizadeh
Automated reconstruction of high-quality genome-scale models using machine learning (b.sc. or m.sc.) background genome-scale metabolic models (gems) are essential in biological research and biotechnological development, as they enable the comprehensive analysis of metabolic networks and fluxes. reconstructing a high-quality genome-scale model (gem) involves a detailed workflow of 96 steps (6). despite the standard protocols and operating procedures available for gem construction, the process remains time-consuming. this has led to recent efforts aimed at automating the reconstruction steps. researchers have developed various protocols that combine automated steps to streamline the reconstruction and refinement of gems. in recent years, machine learning (ml) has played a significant role in the reconstruction and analysis of gems, enhancing their quality and accuracy (1, 4). objective: this project aims to develop an automated protocol for reconstructing high-quality genome-scale models using available ml approaches. we have compiled all available literature focusing on the application of ml in the reconstruction of gems. by integrating these ml-based methods into a cohesive automated procedure, we intend to facilitate the reconstruction and refinement of gems. methodology: 1. literature review and compilation: gather and analyze literature on ml approaches used in gem reconstruction. 2. automation protocol development: combine the identified ml-based steps into an automated workflow. 3. comparison and selection: in the first step, for organism with multiple annotated genomes, for instance, compare the annotations and select the most comprehensive one. 4. gem reconstruction: apply the automated protocol to reconstruct the gem. 5. refinement using ml: to refine the reconstructed gem, employ ml algorithms such as gapfill, pathway tool prediction (2), gene essentiality (5), ec numbers (3), etc. expected outcome: this project will result in an automated, ml-based protocol for gem reconstruction. it will allow for comparing different ml approaches and improve the efficiency and quality of gems. reference: 1. kim, yeji, gi bae kim, and sang yup lee. "machine learning applications in genomescale metabolic modeling." current opinion in systems biology 25 (2021): 42-49. 2. dale, joseph m., liviu popescu, and peter d. karp. "machine learning methods for metabolic pathway prediction." bmc bioinformatics 11 (2010): 1-14. 3. ryu, jae yong, hyun uk kim, and sang yup lee. "deep learning enables high-quality and high-throughput prediction of enzyme commission numbers." proceedings of the national academy of sciences 116.28 (2019): 13996-14001. 4. zampieri, guido, et al. "machine and deep learning meet genome-scale metabolic modeling." plos computational biology 15.7 (2019): e1007084. 5. hasibi, ramin, tom michoel, and diego a. oyarzún. "integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality." npj systems biology and applications 10.1 (2024): 24. 6. thiele, ines, and bernhard ø. palsson. "a protocol for generating a high-quality genome-scale metabolic reconstruction." nature protocols 5.1 (2010): 93-121. contact: dr. reihaneh mostolizadeh, comparative genome analysis of streptococcus agalactiae (gbs) from elephants (m.sc.).
Background Group B Streptococci are fairly common. In livestock, they are the causative agent of an udder inflamation, most often seen in dairy cows.
In elephants, S. agalactiae is associated with Paronchya. Under human care, elephants are known to reach a high age. This comes with an age-related decline in their immune system, which can lead usually harmless skin- or foot diseases to become chronic. Gaining a better knowledge about the bacterial infections is a vital foundation for optimized treatments and therapeutic approaches.
In a newer study done by the "Hessische Landeslabor" (Hesse state labratory (LHL)), some S. agalactiae isolates were compared, using microbiological methods and had extensive biochemical profiles created. Noticable was the high number of isolates, for which the serotypes could not be determined. For this reason some isolates got sequenced, so a full comparative genome analysis could be done, using the latest methods in bioinformatics.
Thesis aims
- Implementation of typical bioinformatic analyses (Assembly, mapping, annotation...)
- Comparative analysis of GBS Isolates (ABR, pan- and coregenome, virulence factors...)
- Closer inspection of Genes for serotyping
Prerequisites
- Interested in solving biological/veterenary questions by usage of bioinformatics
- Extensive knowledge of the Linux command line
- Ability to work independently and methodical
Contact: Linda Fenske
Workflow Design (Nextflow) (M.Sc.)
Analysing (bacterial) sequence data for biological/medical questions means often repeating certain standard processes (QC, Assembly, Annotation etc.)
For better reproduceability and simplification of these processes, flexible pipelines with a wide palette of tools are used. Often Nextflow (of similar workflow tools) is used to enable support for a variety of enviroments or to simplify the installation.
With DSL2, Nextflow recently introduced a significant development of the Nextflow language, which promises a better scalability and modulariziation of pipelines, along with a better design of workflows.
- Revision and updating of an existing workflow for analysing bacerial data
- Transmission of the workflow from nf-DSL1 to DSL2
- Visualising the results (creating a GUI)
Prerequisites
- Knowledge of Nextflow or motivation to become acquainted with Nextflow
- Programming knowledge in Python, Groovy (Nextflow) or similar
- Knowledge and interest in visualisation and processing of data
Platon Bioinformatics Tool Enhancement for Faster Plasmid Identification (M.Sc.) - taken
Modern high-throughput sequencing devices enable the rapid determination of sequence data obtained from interacting microbial communities without a prior cultivation step. Hereby, access to genetic information from otherwise unculturable microbiota is easily achieved. (Computational) Interpretation of such data relies on either assignment of raw sequencing reads to corresponding source organisms in order to infer their taxonomic origin or gene-coding content, or, these metagenome datasets can be assembled, thereby recovering longer contiguous DNA stretches of the underlying microbial genomes.
Assembled metagenomic contigs are typically clustered (most often, depending on coverage or nucleotide composition), yielding individual draft or complete genomes of novel bacterial species. In this process, however, contigs of non-chromosomal origin such as plasmids are often overlooked.
Still, the analysis of plasmids is of utmost imoprtance, since they constitute a key mechanism of horizontal gene transfer between microbial hosts. They are known to harbor essential genes that are beneficial or important for microbial fittness or survival under certain environmental conditions (e.g. in the presence of certain antimicrobial agents) or perform metabolic processes that they otherwise wouldn‘t have been able to (e.g. degradation of novel substrates).
Several bioinformatics applications have been developed for the computational identification of plasmid-borne contigs, most typically focusing on the extraction of plasmid contigs from the assemblies of individual draft genomes. Among these tools are Platon (Schwengers et al., 2020), PlasClass (Pellow et al., 2020) and PlasFlow (Krawczyk et al., 2018), of which Platon exhibits excellent performance, but its runtime characteristics currently impede its application to potentially large metagenome assemblies.
- Overhaul of the Platon code base, switching from a contig-centered approach to one based on bulk data processing in order to significantly decrease overall runtime.
- Inlining of certain sub-analysis steps such as circularity testing into the python codebase instead of relying on the invocation of external tools: (Pyrodigal, pyHMMER, PyTrimal)
- Conditional tool execution: Do not invoke additional tools if preceding steps already exclude a sequence from being a plasmid
- Runtime and performance assessment with regard to the original implementation
Requirements
- Familiarity with Linux and (modular) python programming (incl. unit testing)
- Methodological way of working
- Able to work independently
Contact: Oliver Schwengers
Develop and Compare Curare Modules for Different DGE Libraries (M. Sc)
Differential gene expression analysis (DGE) is a commonly used method in RNA sequencing, in which the expressions of different genes in samples from different conditions are statistically compared to identify relevant genes in stress or defense situations. To simplify the execution of these analyses, the software Curare was developed.
Currently, the R library DESeq2 is used for the statistical evaluation of expression data, but there are also alternative libraries such as edgeR or Limma that pursue similar or completely different statistical approaches.
This Master's thesis aims to write, compare, and combine Curare modules for various DGE libraries. This requires working with different R libraries, integrating the evaluation into Curare (written in Snakemake), and visualizing the results in an HTML report.
- Write Curare modules for different DGE libraries and compare and combine them.
- Learn about different R libraries for statistical analysis of expression data.
- Integrate the analysis in Curare (written in Snakemake) and visualize the results in an HTML report.
Contact: Patrick Blumenkamp
Reconstruction and visualization of KEGG metabolic pathways in the EDGAR platform (M.Sc.)
EDGAR is a web-based platform for analyzing microbial data. It is developed by employees of the Bioinformatics and Systems Biology department at JLU Giessen and provides multifaceted methods for investigating genomes.
KEGG ( Kyoto Encyclopedia of Genes and Genomes) provides curated databases and resources for (among other things) the functional annotation and classification of genes. In previous projects, KEGG functional categories for all organisms and their corresponding genes were computed in the EDGAR platform. These are currently displayed directly in two analysis modules, in purely quantitative terms.
MinPath is a program for reconstructing biological/metabolic pathways. It attempts to infer a minimal biological metabolic network by excluding redundant metabolic pathways that can explain the genes found in a given dataset. The above-mentioned KEGG categories will be used as input for this program.
The goal of the project is to develop a comparative analysis module, based on KEGG pathway information, for the EDGAR platform.
Thesis Aims
- Parse the available KEGG data in a structured manner and compute KEGG metabolic pathways for all given genomes in EDGAR using MinPath.
- Design comparative visualizations for the EDGAR frontend using the resulting data, allowing users to interactively explore their data (see fig. 4 here as an example)
- Adjust the project scope in consultation with the student depending on the project status to accommodate shared ideas, as EDGAR incorporates a wide selection of data with potential for creative analysis methods.
Requirements
Programming skills in Python and JavaScript (can also be learned during the process)
Basic SQL database knowledge
PlasmidHunter: Validation of a metagenome-based plasmid search using public plasmid sequences (M.Sc.)
Plasmids play an important role in the genetic variability of organisms. They replicate independently and between organisms - within and between species. Therefore, plasmids are key drivers of horizontal gene transfer. Often, they are the effective and only difference between commensal and pathogenic bacterial strains. In recent years, it became obvious that plasmids belong to the main mechanisms for the dissemination of antimicrobial resistances and hence are of special interest in medical microbiology. Detecting plasmids and analyzing their dissemination is an important epidemiological and scientific topic that might help to detect current and prevent future outbreaks of antibiotic resistances.
One promising data source containing known and unknown plasmids are whole-metagenome datasets of samples from different sources (soil, waste water, the human gut). For many of these samples, sequencing data is freely accessible in public databases, often annotated with additional meta information such as date, source and location of each sample.
Our project processes these datasets from the MGnify database in a standardized way via modern cloud technologies and makes them accessible to users for a fast search of new plasmids within this huge amount of data.
This master thesis should validate this search via existing plasmid databases (such as PLSDB) and analyze search results including comprehensive visualizations.
- Implementation of a workflow to process PLSDB entries with our existing search workflow
- Statistical analysis of the results, and screen for potential interesting candidates for further analysis
- Visualization of the results
- Knowledge of command line tools and Python
- Interest in cloud technologies
- Prior experience with workflow systems, like Nextflow or Snakemake
Contact: Sebastian Beyvers
Webservice for searching gene families in plants (M. Sc.)
The input is a list of protein sequences. In step 1a, a Pfam search is performed with the sequences to find common domains. In step 1b, a multiple sequence alignment of the sequences is calculated. The conserved regions are automatically extracted from the alignment to calculate HMMs. In step 2, the HMMs of the domains from 1a and 1b are used to search a database of plant proteins.
- The results are visualized and made available for download
- Steps 1 and 2 are also provided as a command-line tool
- The programming language(s) and frameworks can be freely chosen
- Test data will be provided
Contact: Oliver Rupp
R ibosomal binding site prediction based on 16S-rRNA (M.Sc.)
Bacterial translation is initiated by the assembly of ribosomal proteins as part of the translation initiation complex at the coding sequence (CDS) start site. For most CDS, there is a ribosomal binding site (RBS) immediately upstream of the gene, consisting of a 5-10bp spacer and a (partial or complete) Shine-Dalgarno sequence (SD) 5’-AGGAGG-3’ to which the ribosome binds. However, some genes have neither an SD nor a known RBS and are still expressed (Omotajo, D. et al. , 2015) . The Shine-Dalgarno sequence was first described in E. coli but is found in many bacterial genomes and is complementary to the anti-SD sequence at the 3′-end of 16S-rRNA.
The exact Shine-Dalgarno and spacer sequences vary between bacterial species. However, because the anti-Shine-Dalgarno sequence is present in the 16S-rRNA of each bacterial genome, it can be used to predict RBS in a species-independent manner. Therefore, a deep learning approach using the 16S-rRNA sequences and the sequence upstream of the CDS is promising for accurately predicting the presence of RBS independent of species-specific variants.
- Design and implementation of a neural network for ribosomal binding site prediction in bacteria,
- evaluation of the features used by the neural network, and
- analysis of the presence of RBS in exemplary bacterial genomes
- Prior experience with deep learning frameworks such as Tensorflow/Keras, or willingness to learn them
- Prior experience in the development of documented code and dependency management or willingness to learn them
Contact: Julian Hahnfeld
Integrative Omics FAIR Workflow (M.Sc.) Background
Processing and analysing 'omics data often requires applying predefined building blocks of code, i.e. for performing quality control, statistical analysis or machine learning. However, biologists and ecologists are often overwhelmed with the technical complexity of programmatic approaches and interfaces. Hence, scientific workflows can not just automate, but also facilitate important re-occuring processes in high-throughput 'omics analysis.
The existing modularized iESTIMATE pipeline aims at automating and facilitating the complex analysis of ecological metabolomics data and the integration with other phenomics and preparation for sequencing and (meta-)genomics data. The central aim of the pipeline is to extract so called molecular traits that explain molecular mechanisms in plants or microorganisms. Thesis Aims
- Revision and modularisation of existing code to create the R package "iESTIMATE"
- Implementing a workflow in NextFlow or Common Workflow Language (CWL) using test data, implementing unit tests and capture provenance information
- Publish R package and the workflow following the FAIR principles
- Knowledge of R and a bit of Python
- Knowledge of Linux command line, containers, NextFlow (Groovy), YAML, or motivation to become acquainted with them
- Keen interest in analysis of integrative 'omics data and in topics in molecular ecology
Contact: Kristian Peters
Medical Bioinformatics and Computational Modelling
PhD students at the Bioinformatics Laboratory
In Progress
- Lashgari, D. Kinetic maturation in the Germinal Center . University of Amsterdam, Amsterdam. Supported by AMC. Van Kampen, A.H.C. (promotor), Van Gils, M. (co-promotor), Hoefsloot, H. C. (co-promotor).
- Mahamune, U. Single Cell RNAseq and computational modelling . University of Amsterdam, Amsterdam. ARCAID . Marie Curie COFUND, Horizon 2020. Van Kampen, A.H.C. (promotor), Moerland, P.D. (co-promotor), E.G.M. van Baarsen (co-promotor).
- Valiente, R. G. Development of multiscale mathematical models of the germinal center (GC) to study its role in B-cell lymphoma (BCL) and/or rheumatoid arthritis (RA). (PhD thesis). University of Amsterdam, Amsterdam. COSMIC . Marie Curie ITN, Horizon 2020. Van Kampen, A.H.C. (promotor), De Vries, N. (promotor), Hoefsloot, H. C. (co-promotor), Guikema, J. E. (co-promotor).
- Stobbe, M. (2012). 18 October 2012. The road to knowledge: from biology to databases and back again. University of Amsterdam, Amsterdam. NBIC BioRange. Van Kampen, A.H.C. (promotor), Moerland, P. D. (co-promotor). [ UvA-DARE ]
- Shahand, S. (2015). 29 October 2015. Science gateways for biomedical big data analysis. University of Amsterdam, Amsterdam. COMMIT. Van Kampen, A. (promotor), Olabarriaga, S. (co-promotor). [ UvA-DARE ]
- Reshetova, P. (2017). 2 March 2017. Use of Prior Knowledge in Biological Systems Modelling. University of Amsterdam, Amsterdam. NBIC Biorange. Van Kampen, A.H.C (promotor), Smilde, A. (promotor), Westerhuis, J. (co-promotor). [ UvA-DARE ]
- Tejero Merino, E. (2022). 7 November 2022 Multiscale modelling of plasma cell differentiation in the Germinal Center. University of Amsterdam, Amsterdam. Supported by AMC. Van Kampen, A.H.C. (promotor), Guikema, J.E.J. (co-promotor), Hoefsloot, H. C. (co-promotor). [ PhD thesis] [ UvA-DARE ]
- Nandal, U. (2023). Computational approaches for biological data integration. University of Amsterdam, Amsterdam. NBIC BioRange. Van Kampen, A.H.C. (promotor), Moerland, P.D. (co-promotor). [ UvA-DARE ]
- Balashova, D. Repertoire sequencing . University of Amsterdam, Amsterdam. ARCAID . Marie Curie COFUND, Horizon 2020. Van Kampen, A.H.C. (promotor), De Vries N. (promotor), Greiff V. (co-promotor). – Terminated
Co-supervised PhD students from other research groups
In Progress
- Balzaretti, G. Repertoire Sequencing . University of Amsterdam, Amsterdam. De Vries, N. (promotor), Van Kampen, A.H.C. (promotor).
- Lermo Jimenez, M. Epigenetics and breast cancer drug resistance . University of Amsterdam, Amsterdam. Verschure P. J. (promotor), Moerland, P.D. (co-promotor).
- Olivieri, A. Repertoire Sequencing. University of Amsterdam, Amsterdam. ARCAID , Marie Curie COFUND, Horizon 2020. De Vries, N. (promotor), Van Kampen, A.H.C. (promotor).
- Stratigopoulou, M. Germinal Center and B-cell Lymphoma . University of Amsterdam, Amsterdam. COSMIC. Marie Curie ITN, Horizon 2020. Van Kampen, A.H.C. (promotor), Van Noesel, C. J. (promotor), De Vries, N. (co- promotor), Guikema, J. E. (co-promotor).
- Sontrop, H. (2015). 15 January 2015. A critical perspective on microarray breast cancer gene expression profiling. TU Delft, Delft. NBIC BioRange. Reinders, M. (promotor), Moerland, P. D. (co-promotor). [ Link ]
- Beckman, W. (2021). 17 August 2021. The Role of Epigenetics in Transcriptional Stochasticity and the Implications for Breast Cancer Drug Resistance . University of Amsterdam, Amsterdam. EpiPredict. Marie Curie ITN, Horizon 2016. Verschure P.J. (promotor), Van Kampen, A.H.C. (promotor). [ UvA-DARE ]
- Barros, R. S. (2022). 1 November 2022 High performance computing for clinical medical imaging . University of Amsterdam, Amsterdam. Henk Marquering (promotor), Van Kampen, A.H.C. (promotor), Olabarriaga, S. (co-promotor). [ UvA-DARE ]
- Anang, D. (2023) 6 November 2023. B and T Cell Immune Responses in Rheumatoid Arthritis and Myositis. In Search for the Immunological Drummers and Dancers . University of Amsterdam, Amsterdam. COSMIC . Marie Curie ITN, Horizon 2020. De Vries, N. (promotor), Van Kampen, A.H.C. (promotor), van Baarsen, E.G.M. (co-promotor). [ UvA-DARE ]
- Wegdam, W. (2024). In search of protein biomarkers in ovarian cancer and Gaucher disease. University of Amsterdam, Amsterdam. Aerts J.M.F.G. (promotor), Kenter, G.G. (promotor), Moerland, P.D. (co-promotor). [ UvA-DARE ]
- Pollastro, S (2024) 17 May 2024. Understanding Response to Rituximab Treatment in Rheumatoid Arthritis Through Immune Fingerprinting of T and B Cells . University of Amsterdam, Amsterdam. De Vries, N. (promotor), Van Kampen, A.H.C. (co-promotor). [ UvA-DARE ].
Related Posts
PhD thesis Umesh Nandal
compendiumdb
Participation in single-cell genomics 2022 conference
PhD thesis Elena Merino Tejero
Group Leader
Prof. dr. AHC van Kampen
[email protected] https://bioinformaticslaboratory.eu
Amsterdam UMC – location AMC Department of Epidemiology and Data Science Bioinformatics Laboratory Meibergdreef 9 1105 AZ Amsterdam Zuidoost The Netherlands
How to get to us: [ pdf ] [ Google Maps ]
Epidemiology & Data Science
The Bioinformatics Laboratory is part of EDS
Read our Privacy Policy
Bioinformatics Laboratory – Your partner in bioinformatics and computational modelling since 1997
Privacy Overview
| Cookie | Duration | Description |
|---|---|---|
| cookielawinfo-checkbox-analytics | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics". |
| cookielawinfo-checkbox-functional | 11 months | The cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional". |
| cookielawinfo-checkbox-necessary | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary". |
| cookielawinfo-checkbox-others | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other. |
| cookielawinfo-checkbox-performance | 11 months | This cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance". |
| viewed_cookie_policy | 11 months | The cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data. |
Go to Charlotte.edu
Prospective Students
- About UNC Charlotte
- Campus Life
- Graduate Admissions
Faculty and Staff
- Human Resources
- Auxiliary Services
- Inside UNC Charlotte
- Academic Affairs
Current Students
- Financial Aid
- Student Health
Alumni and Friends
- Alumni Association
- Advancement
- Make a Gift
Dissertation Archive
All UNC Charlotte dissertations and theses can be found in ProQuest University of North Carolina at Charlotte .
Dissertations of past Ph.D. students from the Bioinformatics program.
Adam Price: Ph.D., Bioinformatics and Computational Biology Understanding Bias in Next-Generation Sequencing Technologies and Analyses
Benika Hall: Ph.D., Bioinformatics and Computational Biology Constructing microRNA eQTL Networks Using Integrative Network Learning Approaches in Cancer
Rosario Ivetth Corona de la Fuente: Ph.D., Bioinformatics and Computational Biology Structural Analysis of Protein-DNA Binding Specificity and its Application to Protein-DNA Docking Assessment Library
Sajedeh Safari: Ph.D., Bioinformatics and Computational Biology Evolution of Flavonoid Pathway in Legumes Library
Adam Michael Whaley: Ph.D., Bioinformatics and Computational Biology Genetic Mechanisms of Ozone Tolerance in Soybean and Methods of Evolutionary Distance Library
Yan Ni: Ph.D., Bioinformatics and Computational Biology Data Analysis Workflow for Gas Chromatography Mass Spectrometry-Based Metabolomics Studies Library
Meng Niu: Ph.D., Bioinformatics and Computational Biology De Novo Prediction of Cis-Regulatory Modules in Eukaryotic Organisms Library
Jaime Lynn Sheridan: Ph.D., Bioinformatics and Computational Biology Elucidation of Mirnas in Avena Sativa Library
Saeed Khoshnevis: Ph.D., Bioinformatics and Computational Biology The Effect of Structure in Short Regions of DNA on Measurement on Short Oligonucleotide Microarry and Ion Torrent PGM Sequencing Platforms Library
Jonathan Ward McCafferty: Ph.D., Bioinformatics and Computational Biology Microbial Contributions to Disease Phenotypes Library
Shatavia Sharday Morrison: Ph.D., Bioinformatics and Computational Biology Vibrio Vulnifcus Virulence and Survival Mechanisms Revealed through Comparative Microbial Genomic Analysis Library
Cristina Baciu: Ph.D., Bioinformatics and Computational Biology Bioinformatics and Biomolecular Tools for biomarker discovery in peripheral blood lymphocytes from patients with sporadic amyotrophic lateral sclerosis Library
Charles David: Ph.D., Bioinformatics and Systems Biology Time Delayed Dynamical Systems and the Duffing Equation Library
Verma Deeptak: Ph.D., Bioinformatics and Computational Biology Elucidating the Effects of Mutation and Evolutionary Divergence Upon Protein Structure Quantitative Stability/Flexibility Relationships Library
Christopher C Overall: Ph.D., Bioinformatics and Computational Biology Microarray Tools and Analysis Methods to Better Characterize Biological Networks Library
Luis Gonzalez: Ph.D., Bioinformatics and Systems Biology A Virtual Pebble Game to Ensemble Average Graph Rigidity Library
Nina Sanapareddy: Ph.D., Bioinformatics and Systems Biology Using Bioinformatics to Analyze the Role of Microbial Taxa in Complex Ecosystems Library
Melanie Spencer: Ph.D., Bioinformatics and Systems Biology Stability, Resistance and Change in Mammalian Microbiota and Their Associations With Host Health Library
Timothy Tickle: Ph.D., Bioinformatics and Systems Biology Data Mining the Serous Ovarian Tumor Transcriptome Library
Vladyslava Ratushna: Ph.D., Bioinformatics ans Systems Biology The Effect of Target Secondary Structure on Microarray Data Quality Library
Robert Reid: Ph.D., Bioinformatics and Systems Biology Improving Data Extraction Methods for Large Molecular Biology Datasets Library
Raad Gharaibeh: Ph.D., Bioinformatics and Systems Biology Studies on the Relationships Between Oligonucleotide Probe Properties and Hybridization Signal Intensities Library
- Director’s Welcome
- Participating Departments
- Frontiers in Computational Biosciences Seminar Series
- Current Ph.D. Students
- Current M.S. Students
- Bioinformatics Department Handbook
- B.I.G. Summer Institute
- The Collaboratory
- Diversity and Inclusiveness
- Helpful Information for Current Students
- Joint UCLA-USC Meeting
- Student Blog and Twitter Feed
- Social Gatherings
- Introduction to the Program
- Bioinformatics Admissions Information
- Admissions FAQs
- Student Funding
- Curriculum and Graduate Courses
- Research Rotations
- Qualifying Exams
- Doctoral Dissertation
- Student Publications
- Admissions Information
- Capstone Project
- Undergraduate Courses
- Undergraduate and Masters Research
- Bioinformatics Minor Course Requirements
- Bioinformatics Minor FAQs
- Bioinformatics Minor End-of-Year Celebration
- For Engineering Students
Thesis Preparation and Filing: Staff from the University Archives and the UCLA Graduate Division present information on University regulations governing manuscript preparation and completion of degree requirements. Students should plan to attend at least one quarter before they plan to file a thesis or dissertation. More information is found at https://grad.ucla.edu/gasaa/library/thesisintro.htm
The official UCLA manuscript preparation guide for PhD Dissertations can be found at https://grad.ucla.edu/gasaa/etd/thesisguide.pdf
Featured News
Researchers awarded $4.7 million to study genomic variation in stem cell production, dr. nandita garud recognized for her research on gut microbiome, ucla study reveals how immune cells can be trained to fight infections, ucla scientists decode the ‘language’ of immune cells, dr. eran halperin elected as fellow of international society for computational biology, upcoming events, labor day holiday, recent student publications.
RECENT STUDENT PUBLICATIONS LINK-PLEASE CLICK!
Updates Coming Soon!
Systems Biology and Bioinformatics Group
Department of Information Engineering – University of Padova
Thesis topics
Are you a Bachelor or Master’s student looking for a thesis topic in Bioinformatics and Machine Learning on clinical data?
Here you can find topics that may interest you. SysBioBig will be glad to help you explore the topics that most stimulate your interest.
In-silico models of the interaction between immune system and tumor cells informed by sequencing data
Recently, several computational modeling approaches have been applied to study and simulate the interaction dynamics between immune and tumor cells in human cancer. However, each tumor is characterized by a specific and unique tumor microenvironment (TME), emphasizing the need for specialized and personalized studies of each cancer scenario. Theses on this topic will focus on developing computational models to simulate cancer progression using multi-agent based models to simulate the interactions between immune system cells and tumor cells, as well as the effects of treatments, and their implementation in a Python package. Data mining techniques and bioinformatics tools will be used to analyze patient specific sequencing data and thus simulate patient specific tumor progression and treatments.
Keywords : agent-based model, spatio-temporal evolution, tumor microenvironment, single-cell, data-driven, Python, R, Git/Gitlab, Docker
Development of bioinformatics methods for the analysis of cell-cell communication from single cell RNA-sequencing data
In complex organisms, the interaction between different cell types has a major role in controlling and coordinating cellular activities, such as tissue and organ development and function. For the first time ever, the advent of single cell RNA sequencing has enabled the possibility to study cellular communication in an high-throughput way. However, the bioinformatics analysis of cell communication from scRNA-seq data is a quite young and fast evolving research area, and much work has still to be done to improve the quality of current bioinformatics analyses. Theses on this topic will focus on developing computational models to infer cell-cell communication from sequencing count data.
Keywords : scRNA-seq, cell-cell comunication, signaling networks, reverse engineering, differential cellular communication, R, Python, Git/GitLab, Docker
Robust identification and simulation of biomarkers in RNA-sequencing and metagenomic data
The development of increasingly efficient and cost-effective sequencing techniques has enhanced the possibility of studying complex microbial systems. Mining microbiome data, however, requires specific computational methods to extract the information useful for analysing the micro-world of interest. Another recent sequencing technology, Single-cell RNA-sequencing (scRNA-seq) has emerged in the last decade. scRNA-seq is a powerful technique for profiling the transcriptomes at the single-cell resolution, i.e. the amount of mRNA (expression level) of each gene transcribed in each individual cell. Microbiome and scRNA-seq data show some characteristics in common. Consequently, bioinformatics analysis methods coming from the RNA-seq field can be used to perform microbiome analysis. However, although many methods have led to important conclusions in different fields, the lack of a known biological truth makes it impossible to validate the results obtained in both contexts. Theses on this topic will focus on evaluation of bioinformatics methods for biomarkers discovery in sequencing data.
Keywords : scRNA-seq, microbiome, differential abundance, differential expression, simulation, benchmarking, R, Git/GitLab, Docker
Implementation of a Python simulator for microbial communities’ evolution via agent-based modeling
Modeling microbial communities’ evolution has gained immense importance in many scientific fields, from agronomy and food science to human medicine and even material engineering. However, such an interconnected system composed of several molecules and a plethora of bacterial species requires advanced modeling techniques to catch the intrinsic complexity. Agent-based modeling can be exploited to model bacterial communities: by decomposing the complexity of the system in a simpler description of each species with its own decoupled behavior, we aim to simulate a system in which peculiar ecological mechanisms such as commensality or amensalism rises from a model-free interaction. While the overall model structure and a preliminary GUI has already been drafted, many improvements still need to be implemented.
Keywords : Agent-based modelling, microbial community, Python, Dash, Git, GitLab
- Privacy Overview
- Strictly Necessary Cookies
This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.
Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.
If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.
- DigitalGeorgetown Home
- Georgetown University Institutional Repository
- Georgetown University Medical Center
- Biomedical Graduate Education
- Department of Biostatistics, Bioinformatics & Biomathematics
Graduate Theses and Dissertations - Biostatistics, Bioinformatics & Biomathematics
Creators Titles By Creation Date
Search within this collection:
Browse All Items
Most Recent Submissions
Deconvolution Analysis and Differential Expression Inference for Bulk Tissues and Spatial Transcriptomics
Contributions to Parametric and Semiparametric Structural Equation Modeling Methods with Applications in the Biomedical Sciences
Enhanced Doubly Robust Estimation for Group Comparisons in Presence of Missing Data and Time-varying Confounders
Functional Data Analysis and its Application in Biomedical Research
Effective Semiparametric Analysis for Causal Inference with Time-to-Event Outcomes
Your browser is unsupported
We recommend using the latest version of IE11, Edge, Chrome, Firefox or Safari.
Richard and Loan Hill Department of Biomedical Engineering
Colleges of engineering and medicine, dnc impact on campus, ms in bioinformatics.
Required Semester Hours: 36
Thesis track Heading link Copy link
The thesis track is designed for MS in Bioinformatics students who are interested in conducting research. This track is strongly advised if you may be interested in pursuing a PhD in the future.
Researching and writing a master’s thesis is an academically intensive process that takes the place of 8 credits of traditional coursework. Students work with a faculty advisor to choose a topic of interest, engage in high-level study of that topic, and develop a paper that is suitable for presentation at a conference or submission to a journal.
The thesis experience provides definition to your master’s degree experience and can bolster your application for jobs or doctoral-level study by demonstrating your capabilities.
In the thesis option, you will earn 8 credits in BME 598 Master’s Thesis Research and at least 28 credit hours from coursework. At least 12 of your coursework credits must come from courses at the 500 level, excluding BME 595, BME 596, and BIOE 598. You may be allowed limited credit hours from BME 596 Independent Study with department approval. There is no comprehensive examination.
Recent UIC master’s thesis projects in bioinformatics include:
thesis titles Heading link Copy link
Nikita Dsouza
Strategies for Identification of Small Molecule Inhibitors of Ad2 E3-19K/HLA-A2 Binding Interaction
A Statistical Framework for GeneSet Enrichment Analysis based on DNA Methylation and Gene Expression
Navya Josyula
Identifying Ligand Binding Sites of Proteins using Crystallographic Bfactors and Relative Pocket Sizes
Non-thesis track Heading link Copy link
In the non-thesis track, you earn all of your required 36 credit hours from coursework. Of these, 16 must be from courses at the 500 level. There is no comprehensive examination.
Across-the-board requirements Heading link Copy link
- 1 hour of BME 595
- Present at least one seminar (BME 595) before graduation
- Students entering the program without an undergraduate degree in bioengineering or biomechanical engineering must also take BME 480, BME 481, and BME 530
MS alumni in their own words Heading link Copy link
Daiqing Chen ’21 MS in Bioinformatics
What led you to choose bioinformatics for your MS degree? How do you think computational technology is changing biomedical engineering? I was doing molecular biology during my undergrad. Wet lab experiments are very time- and money-consuming. I have seen people using bioinformatics methods to solve biological questions, and I want to be able to use them. I actually don’t know much about engineering, but I believe a computational method can be useful for any field. The high efficiency allows people to do more things than ever before.
What are your plans for once you have completed your degree? I am planning on working as a research assistant in biological lab, most likely doing research about cancer. My time at UIC helped me get more familiar with American culture.
Have you worked in any labs? Yes, the Computational Functional Genomics Laboratory . I did a project to validate machine learning models that predict kidney function decline. I also worked on high-throughput single-cell sequence analysis.
Your primary hobby/outside interest: Playing badminton.
Favorite restaurant in Chicago: Minhin’s cuisine for the dim sum.
Additional information Heading link Copy link
- MS in Bioinformatics course checklist: thesis track
- MS in Bioinformatics course checklist: non-thesis track
- MS in Bioinformatics graduate catalog page
- UIC Graduate College admissions
- Important deadlines for BME graduate students
| to post a comment. --> --> --> --> --> --> --> --> --> --> --> --> --> | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| University of Southern California | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
IMAGES
COMMENTS
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.
MSc thesis: In the Bioinformatics group, we offer a wide range of MSc thesis projects, from applied bioinformatics to computational method development. Here is a list of available MSc thesis projects.Besides the fact that these topics can be pursued for a MSc thesis, they can also be pursued as part of a Research Practice.. BSc thesis: As a BSc student you will work as an apprentice alongside ...
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; 210 views Submission open
This project will assess whether AMGs generally evolve into distinct shorter versions of the bacterial gene and whether the transfer of metabolic genes from phages to bacteria is a prevalent phenomenon. To this end, publicly available genomes of phages and bacteria will be scanned for metabolic genes (Shaffer et al. 2020).
Bioinformatics. Bioinformatics. 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 ...
Open thesis topics. Within our group we can offer various topics in the field of applied bioinformatics, high-throughput data analysis, genome and metagenome research as well as postgenomics and systems biology. Below you can find a list of suggested open topics for BSc and MSc theses and student projects.
PhD Theses PhD students at the Bioinformatics Laboratory In Progress Lashgari, D. Kinetic maturation in the Germinal Center. University of Amsterdam, Amsterdam. Supported by AMC.
All UNC Charlotte dissertations and theses can be found in ProQuest University of North Carolina at Charlotte. Dissertations of past Ph.D. students from the Bioinformatics program. 2017 Adam Price: Ph.D., Bioinformatics and Computational Biology Understanding Bias in Next-Generation Sequencing Technologies and Analyses Benika Hall: Ph.D., Bioinformatics and Computational BiologyConstructing ...
Theses. Thesis Preparation and Filing: Staff from the University Archives and the UCLA Graduate Division present information on University regulations governing manuscript preparation and completion of degree requirements. Students should plan to attend at least one quarter before they plan to file a thesis or dissertation.
However, the bioinformatics analysis of cell communication from scRNA-seq data is a quite young and fast evolving research area, and much work has still to be done to improve the quality of current bioinformatics analyses. Theses on this topic will focus on developing computational models to infer cell-cell communication from sequencing count data.
Functional Data Analysis and its Application in Biomedical Research . Li, Haiou (Georgetown University, 2023) The objective of the dissertation is to develop new statistical methods for functional data analysis motivated by several biomedical research. In many applications with functional observations, the main goals of statistical ...
The thesis track is designed for MS in Bioinformatics students who are interested in conducting research. This track is strongly advised if you may be interested in pursuing a PhD in the future. Researching and writing a master's thesis is an academically intensive process that takes the place of 8 credits of traditional coursework.
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.
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.
The doctoral dissertation will be submitted to each member of the doctoral committee at least four weeks before the final examination. The student will defend his or her final thesis after the committee's evaluation and will pass or fail depending on the committee's decision. PLEASE READ: FAQ on scheduling exams. UCSD Writing Hub's services for ...
In the Master's program in bioinformatics, you must do a 30 ECTS Master's thesis. You must start your 30 ECTS thesis no later than February 1 (or September 1) a year and a half after commencement of your studies (i.e. February 2021 for students admitted in summer 2019, or September 2021 for students admitted in winter 2020).
Must be a graduate student in the Biomedical Sciences PhD Program, in the Bioinformatics Track, and must have approval of instructor/mentor to register for his/her section of the course. Students must take their Qualifying Exam before registering for the Thesis course. 1. Syllabus Template/Revised: July 31, 2019 Office of the Provost/University ...
Master`s Thesis Bioinformatics Masters Degree Programme, Institute of Biomedical Technology University of Tampere, Finland Tommi Rantapero May, 2012 . ii ACKNOWLEDGEMENTS This work has been done in the Genetic Predisposition to Prostate Cancer group lead by Prof. Johanna Schleutker in the Institute of Biomedical Technology, University of ...
Electronic Collections. A number of recent theses and dissertations prepared at Oxford are available to download from the Oxford Research Archive (ORA). The British Library provides access to UK theses through its EThOS service [currently unavailable]. Already digitised UK theses can be downloaded freely as PDF files.
This dissertation aims to design novel machine learning-based models to transform biomedical big data into valuable biological insights. The research presented in this dissertation focuses on three bioinformatics domains: splice junction classification, gene regulatory network reconstruction, and lesion detection in mammograms.
I'm a biotechnology student with interest in bioinformatics. To finish my bachelor's degree, I need to prepare a short thesis (about 15 pages long). Do you guys have any good idea that could fit in this quite small schema. I have some very basic knowledge on this field; I've worked in R (basic statistics) and I know basics of Python (I wouldn't ...
Thesis topic ideas!!! Hi all ! I completed my undergraduate degree in Btech. Bioinformatics this year (passed with 7/10 gpa). Now i am trying to apply for masters in computer science with specialisation in bioinformatics in canada , most of my desired colleges offer thesis based courses and even though i have a couple publications to my name but they were all in a group of 7-8 people so i dont ...
Help on how to decide masters thesis topic. academic. I am doing my masters now and I have to submit a thesis for my program. I am not sure on what topic should I do on . I have the following modules in my bioinfo masters: statistics, omics, machine learning and system biology. 1.Can I have some recommendation on topics which I can do my thesis ...
Recent News. August 12, 2024 Upcoming Dissertation Defenses; August 12, 2024 DFCI Data Science Seminar - 8/13; August 12, 2024 Help Planning 2024 Data Adventure Day; August 12, 2024 HBC 'Upcoming Current Topics in Bioinformatics' Workshop - 8/21; August 12, 2024 2024 PQG Conference Earlybird Registration now open!; August 5, 2024 Du Bois Scholars Program Summer Research Presentations ...
In her role as chair, Guest has led the vision for the conference's speakers and topics, fundraising and grant support, the conference's mentoring program and scholarships, and the pre-conference workshops being held at Rollins today (one where junior investigators meet with NIH program officers to help build successful research programs ...
Schar School of Policy and Government adjunct professor Lee Roberts was recognized as a 2024 Teacher of Distinction by George Mason University's Stearns Center for Teaching and Learning.Roberts, who is a U.S. Army strategic intelligence officer in his 17th year of active-duty service, is the first Schar School adjunct to receive the award since its inception 12 years ago.
But when the COVID-19 pandemic hit, Boland was worried about losing time on his thesis and the possibility of it delaying his graduation. In response, Tim Devarenne, Ph.D., associate head of ...