bioinformatics phd thesis topics

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Bioinformatics & Systems Biology Research Areas

The Bioinformatics & Systems Biology doctoral program covers a wide array of topics to address questions in biomedical research from novel algorithm development to the application of bioinformatics tools for innovative research.

The expertise of the participating faculty members varies widely from pure wet lab research to pure computational research. Students have the option to choose co-mentors to provide bioinformatics and biological expertise or to or work exclusively with one mentor with bioinformatics expertise. Most of the research projects involve bioinformatic data analyses either preceding (hypothesis-generation) or succeeding (hypothesis-testing) an experimental component.

New method or algorithm development in bioinformatics

Active method/algorithm development in the areas of cancer genomics, neuroinformatics, immunoinformatics, microbial metagenomics, structural bioinformatics, graph-theory based biological network analysis, and natural language processing (NLP).

Application of bioinformatics in systems biology research

Research in this area typically involves both experimental and bioinformatics aspects of a project in a basic science research laboratory at UNMC. Broad research topics include analysis of multi-omic datasets (genomics, transcriptomics, proteomics, metabolomics, etc), pathway and network analyses, agent-based modeling, drug repurposing, microbiome characterization in health and disease states, etc.

Mathematical/statistical applications in bioinformatics

Developing novel statistical approaches to study splice variants in human cancers or immunogenicity of protein variants, survival analysis and disease risk prediction using molecular and clinical datasets, mathematical modeling to characterize/visualize high-dimensional experimental data in biology, etc.

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 ].

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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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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

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Bioinformatics and computational biology

Information about a doctoral study programme at charles university with the planned opening in the academic year 2023/2024.

Bioinformatics and computational biology are multidisciplinary disciplines on the interface of computer science (especially algorithms and software development, data engineering), mathematics (especially probability, statistics, and mathematical modeling), and biology (especially molecular and evolutionary) aimed at the development and implementation of algorithms, software tools, and mathematical models for processing, analyzing, and modeling biological data and processes at the molecular and cellular level.

The common denominator of bioinformatics and computational biology, which encompasses diverse areas such as systems biology, neuroinformatics, bioimaging, and computational drug design, is the development of analytical procedures and software tools for processing and analyzing large, domain-specific, and heterogeneous data to understand cellular processes at the molecular level, to learn from the evolution of given processes and eventually apply this knowledge in various fields, especially in medicine and biotechnology.

Pursuing a PhD in bioinformatics offers an opportunity to become an expert in a rapidly evolving field that plays a critical role in advancing our understanding of complex biological systems.

As a bioinformatics PhD student, you will learn cutting-edge techniques for analyzing and interpreting large-scale genomic, proteomic, and metabolomic data, as well as develop computational tools to facilitate data analysis. You will also have the opportunity to collaborate with experts in other fields, such as biology, medicine, and engineering, and work on projects with real-world applications, such as drug discovery and personalized medicine.

Furthermore, pursuing a PhD in bioinformatics can lead to diverse career opportunities, including academia, industry, government, and healthcare. With the growing demand for data-driven solutions in biology and medicine, bioinformatics PhD graduates are highly sought after in both the public and private sectors.

Research areas

Although there is no widely accepted categorization of the domain, for the purpose of our study program, we partition the field into the following non-exclusive categories.

Computational genomics

• Petr Daněček - Sanger / Department of Software Engineering MFF UK
• Michal Kolář - Laboratory of Genomics and Bioinformatics
• Tomáš Pluskal - Biochemistry of Plant Specialized Metabolites
• Lukáš Valihrach - Laboratory of Gene Expression

Structural bioinformatics

• Jiří Černý - Laboratory of Structural Bioinformatics of Proteins
• Klára Hlouchová - Klara Hlouchova Research Group
• David Hoksza, Marian Novotný - Charles University Structural Bioinformatics Group (CUSBG)
• Roman Pleskot - Laboratory of Integrative Structural Biology
• Bohdan Schneider - Bohdan Schneider's Lab
• Jiří Vondrášek - Jiří Vondrášek Group

Computational proteomics

• Pavel Stopka - Lipocalins in Modulation of Mammalian Reproduction

Phylogenetics

• Vladimír Hampl - Evolutionary protistology group

Population genetics

• Radka Reifová - Group of Population and Speciation Genetics

Systems biology

• Petr Baldrian, Tomáš Větrovký - Laboratory of Environmental Microbiology

Neuroinformatics/Computational neuroscience

• Ján Antolík - Computational Systems Neuroscience Group (CSNG)

Bioactive molecule discovery/Computational drug discovery

Molecular modeling.

• Lucie Nová - Department of physical and macromolecular chemistry

Course of study

Unlike Bachelor's or Master's studies, doctoral studies which are more oriented towards on obtaining foundational knowledge and skills and are therefore more course-oriented, PhD studies are highly specialized. To earn a PhD degree you are expected to develop expertise in a specific area of the discipline, to make original contributions to your field of study through independent research, publish the results of your research, write a dissertation about the results, and defend your work. The following sections describe various aspects of the study program.

As we strongly believe that the primary focus of a PhD studies should be on research rather than coursework. Therefore, there is only one obligatory course in the programme, the Doctoral bioinformatics seminar . The idea of the seminar is for students from different fields of bioinformatics and computational biology to share their insights and knowledge, mutually broadening their views and enriching their research with new insights from related areas which are not directly within their direct field of expertise. Additionally, in their first one or two years of the programme, students are expected to take 1-2 courses, which should be chosen to complement their research focus. This will enable them to develop a deeper understanding of their research area and provide them with the necessary tools to conduct high-quality research.

Publications

In order to be allowed to defend doctoral thesis, the student needs to fulfill the following criteria. A deviation from those criteria is possible but will be considered on an ad-hoc basis. The student needs to have least 2 impacted ( WOS or SJR ) journal publications, with at least one having the student as the first (joint first authorship is fine) or corresponding author. In the case of an exceptionally important article in a top journal such as Nature or Science, one publication is sufficient. This requirement can be replaced in exceptional cases by peer-reviewed conferences (a typical publication format in some fields such as computer science), which must be top conferences in the field (on the order of A or A* conferences according to CORE rating ) and quite exceptionally by several manuscripts in Bioarxiv. These results will be recognized ad-hoc.

Doctoral exam

It is expected that the exam will be taken no later than during the 5th semester since starting the doctoral studies. The aim of the examination is to evaluate the work done so far and the progress on the dissertation. The aim is therefore not to test knowledge on the basis of a curriculum of a group of courses or fixed lists of topics. There are 2 reasons for this:

• Given the dynamics of the field, specific topics would need to be updated frequently.
• The programme supports a relatively broad spectrum of topics ("traditional" bioinformatics, systems biology, neuroinformatics, bioimaging, ...) and it is difficult to define the knowledge that can be considered "core" or common across all the areas (the result would be a closest common ancestor that would be somewhere in the realm of graduate or even undergraduate topics).

Therefore, the exam will consist of 2 parts:

• Presentation of the dissertation topic and progress made so far.
• The actual "exam"/discussion, based on the presentation and on the supplied topics (see below).

Bioinformatics and computational biology is an interdisciplinary programme, but each research topic relies on results from computer science/mathematics and biology. The exam will thus consists of these two areas with a focus on the student's research topic. The specific topics will be proposed by the supervisor and presented to the subject area board. As the topic may be far from the expertise of all members of the subject area board that it would be difficult for anyone to test it, 2 experts in areas relevant to the student's research will also be proposed for each examination (these may or may not be recruited from among the subject area board members).

The topic proposal should include

• A general description with a definition of the dissertation topic
• A list of accomplishments and a plan of work
• Relevant literature within the scope of which knowledge is expected at a minimum (i.e., a necessary condition, not necessarily sufficient)

Dissertation thesis

Form of the thesis.

The preferred form of the thesis is an article-based thesis of papers linked by an overarching research question or theme. The thesis should include an overview introduction of approximately 30-50 pages setting the publications in a broader context. The purpose of the introduction is to provide an overview of the research domain and a summary/discussion of the results and own contributions, which are then detailed in the accompanying papers.

Thesis defense

The thesis will be reviewed by two oponnents with at least one being from abroad. The thesis defense will include thesis presentation and discussion.

We strongly believe that pursuing an internship abroad can provide PhD students with numerous benefits, including international experience, exposure to different research methods, a professional network, cultural immersion, and enhanced career prospects. It is an excellent opportunity for students to broaden their horizons, gain new perspectives, and develop a set of skills that will be valuable in their future careers.

For the above reasons, we strongly advise at least a 3-month internship at an abroad institution. If the student does not undergo an internship it needs, the reasons for such a decision need to be explained during the thesis defense.

Admission procedure

Before you apply for the doctoral study programme in Bioinforamtics and computational biology, we strongly advice you to first find an advisor and agree with them on the prospective PhD project. Although it is technically possible to submit an admission application without having an agreed upon supervisor we strongly discourage from taking such path. In order to get accepted for the study programme, you need to apply for the PhD programme either at the Faculty of Mathematics and Physics or Faculty of Science . The choice is basically given by the affiliation of your advisor. Should your advisor not be affiliated with either of the faculties, we suggest to pick Faculty of Mathematics and Physics if the prospective doctoral project is more computationally oriented and Faculty of Science in case of more application oriented project. In any case, you will be pursuing the Ph.D. under the same study board with exactly the same rules, irrespective on the faculty under which you will be officially enrolled. The choice of faculty determines whether you submit your application at the Faculty of Mathematics and physics (following this set of intructions ) or at the Faculty of Science (following this set of intructions ). After you provide all the required documents you will need to pass the entrance interview (the same irrespective of the faculty you applied to). Befor the interview, you will need to prepare and attaches a written (approximately 250-500 words) proposal for a doctoral project (part of the application form). Then, the inteview will be held in English and will have two parts. In the first part, you will present yourself and your doctoral project in a short (max 10 minutes) presentation. In the second part of the examination, the committee will ask three questions. One question will focus on the project itself, and the other two questions will test the orientation in the field regarding the proposed your project's topic and your previous field of study. The committee will evaluate each answer with a Pass/Fail statement. You must receive a Pass for all three answers in order to be accepted for the programme. Additionally you need to demonstrate English language profficiency by passing language examination. This can be waived as described in the admission procedure materials linked above.

• 03/2024 We have been holding the second run of the bioinformatics academia-industry meetup called Bioinformatics - a bridge between industry and academia .
• 02/2024 As part of the Seed4EU+ action within the 4EU+ alliance of European universities, we co-created a joint course on Applications of Deep Learning in Life Sciences ( DeepLife ) involving the universities of Paris-Sorbonne, Warsaw, Prague, Milano and Heidelberg.
• 01/2024 During the academic year 2023/2024 we organized the Meet-EU course, an international team-based course organised by five 4EU+ member universities (Heidelberg, Milan, Paris, Prague, Warsaw) as part of the 4EU+ joint educational offer. This year, we were hosting the final in-person event.
• 05/2023 Programme materials available on the website
• 02/2023 We have been holding a bioinformatics academia-industry meetup called Bioinformatics - a bridge between industry and academia .
• 01/2023 Accreditation application approved by the Faculty of Mathematics and Physics dean's collegium
• 12/2022 Accreditation application finished
• 11/2022 Subject area board established

The study programme is being established with the support of the Czech Recovery Plan, project NPO_UK_MSMT-16602/2022.

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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.

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

We have 252 Bioinformatics PhD Research Projects PhD Projects, Programmes & Scholarships

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Bioinformatics PhD Research Projects PhD Projects, Programmes & Scholarships

Biology of ageing: investigating the effect of novel compounds and genetic interventions on longevity and functionality, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Self-Funded PhD Students Only

This project does not have funding attached. You will need to have your own means of paying fees and living costs and / or seek separate funding from student finance, charities or trusts.

Global Atopic Dermatitis Atlas omics (GADA-omics) project – Identifying skin microbiome, metabolome and host immune marker signatures associated with atopic dermatitis phenotypes

Funded phd project (uk students only).

This research project has funding attached. It is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

Predicting eye disease risk using genetics

Competition funded phd project (students worldwide).

This project is in competition for funding with other projects. Usually the project which receives the best applicant will be successful. Unsuccessful projects may still go ahead as self-funded opportunities. Applications for the project are welcome from all suitably qualified candidates, but potential funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

PhD positions in Computational Biophysics of Protein-Membrane Interactions and Lipid Metabolism - Fribourg, Switzerland

Funded phd project (students worldwide).

This project has funding attached, subject to eligibility criteria. Applications for the project are welcome from all suitably qualified candidates, but its funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

On-therapy monitoring of oesophageal cancer and recurrence detection: the Blood-based Liquid Sequencing Study (BLISS)

A collaborative approach to biomarker discovery for equine grass sickness, competition funded phd project (uk students only).

This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. The funding is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

MScR - Computational pharmacology of GPCRs

Fully funded master by research in biology studentships: analysing datasets in disease models of obesity, generative ai for biodiversity/conservation, developing non-model microorganisms for a net zero future, exploration and development of clinical metagenomics for rapid infection diagnostics, pathogen identification and resistome profiling in advanced chronic liver disease patients, cdts332: understanding the primary drivers for seagrass (zostera marina) regeneration and loss, a novel role in mitochondrial homeostasis for the anti-ageing factor rbbp5, mapping the matrix in tumour progression: integrating digital pathology and 3d biological models, doctoral researcher (m/f/div) in microbiome systems biology.

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	University of Delaware
	Jun 15, 2024   2024-2025 Graduate Catalog     2024-2025 Graduate Catalog Overview of Degree Requirements 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. Students who are admitted directly after a B.S degree will be required to fulfill the Bioinformatics and Computational Biology M.S. core curriculum by completing an additional 9 credit hours as prerequisites (for a total of 24 coursework credits) 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. Students must maintain a 3.0 cumulative GPA and courses with a grade of C or below will not be counted towards the degree. Credit Requirements: Bioinformatics Data Science Core: 9 Credits Prerequisites*: 3-9 Credits Electives: 6 Credits Seminar: 3 Credits Research: 6 Credits Doctoral Dissertation: 9 Credits *Direct Admit Students Total number of required credits: 33-42 A. bioinformatics data science core:, bioinformatics:. BINF 644 - Bioinformatics Credit(s): 3 Data Science - System Biology:: Choose one of the following: BINF 694 - Systems Biology I Credit(s): 3 BINF 695 - Computational System Biology Credit(s): 3 Systems Biology recommended elective upon approval by dissertation committee and Graduate Program Director. Data Analytics: CISC 681 - Artificial Intelligence Credit(s): 3 CISC 683 - Introduction to Data Mining Credit(s): 3 CISC 684 - Introduction to Machine Learning Credit(s): 3 NURS 844 - Population Health Informatics Credit(s): 3 Data Analytics recommended elective upon approval by Dissertation Committee and Graduate Program Director. B. Prerequisites - if required (3-9 credits)* Introduction to discipline:. BISC 609 - Molecular Biology of the Cell Credit(s): 3 BISC 654 - Biochemical Genetics Credit(s): 3 BINF 690 - Programming for Bioinformatics Credit(s): 3 PLSC 667 - Seminar: Applications of Genome Science: From Microbes to Mammals BINF 640 - Databases for Bioinformatics Credit(s): 3 CISC 637 - Database Systems Credit(s): 3 Biostatistics: STAT 611 - Regression Analysis Credit(s): 3 STAT 656 - Biostatistics Credit(s): 3 *Necessary for students lacking equivalent courses C. Electives: Please see list of Elective Courses . D. Seminar: Must enroll in every semester for the first three years and present one seminar in the second and third years. BINF 865 - Seminar Credit(s): 0-1 E. Research: BINF 868 - Research Credit(s): 1-6 - Until successful completion of preliminary exam(1-6) BINF 964 - Pre-Candidacy Study Credit(s): 3-12 - Until successful completion of candidacy exam (1-6) F. Doctoral Dissertation: BINF 969 - Doctoral Dissertation Credit(s): 1-12 Last Revised for 2019-2020 Academic Year Bodleian Libraries Oxford LibGuides Bioinformatics Theses & Dissertations Bioinformatics: Theses & Dissertations Journals and Conference Proceedings Online resources Links for Theses and Dissertations Proquest Dissertations and Theses Search US theses and dissertations. Accessed through OxLip+, search for 'dissertations and theses'. Oxford Research Archive (ORA) Search for and download recent Oxford DPhil theses. Also contains an archive of articles, papers and research posters produced by academics and researchers at Oxford University. more... less... ORA is freely available and does not require a log-in. EThOS Access to UK theses from the British Library [Currently unavailable]. more... less... To use this service you will be required to set up an individual account. DART-Europe Search European E-theses. Theses and Dissertations On-line 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 . Already digitised UK theses can be downloaded freely as PDF files. Requests can be made to digitise older theses, but there is a cost of around £40 and waiting time of 30 days for digitisation. The British Library no longer provides theses on microfilm. Finding Oxford Theses SOLO allows you to search for Theses in the Oxford collections. 1. Navigate to the  SOLO  homepage. 2. Click on the ' Advanced Search ' button 3. Click the ' Resource Type ' menu and choose the ' Theses ' option. 4. Type in the title or author of the thesis you are looking for and click the ' Search ' button. Other Relevant Guides ORA: Oxford University Research Archive by Jason Partridge Last Updated Apr 10, 2024 2397 views this year << Previous: Online resources Last Updated: May 16, 2024 3:04 PM URL: https://libguides.bodleian.ox.ac.uk/bioinformatics Website feedback Accessibility Statement - https://visit.bodleian.ox.ac.uk/accessibility Google Analytics - Bodleian Libraries use Google Analytics cookies on this web site. Google Analytics anonymously tracks individual visitor behaviour on this web site so that we can see how LibGuides is being used. We only use this information for monitoring and improving our websites and content for the benefit of our users (you). You can opt out of Google Analytics cookies completely (from all websites) by visiting https://tools.google.com/dlpage/gaoptout © Bodleian Libraries 2021. Licensed under a Creative Commons Attribution 4.0 International Licence 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. MD | PhD Program Master's Programs PhD Programs Postdoctoral Fellows Residency & Fellowship Non-Degree Programs Visiting Students Campus Life at U-M Health & Wellness Building Your Community Accessibility & Disability Departments Centers & Institutes Interdisciplinary Programs Facts & Figures Medical School Leadership News & Stories Requirements Interview Day Admissions Chats AAMC Michigan's 35 Answers AAMC Michigan's 10 Financial Aid Answers Admitted Students Overview & Highlights Patient Interaction Chief Concern Years 3 & 4 Learning Informatics Training Sites Leadership Program Global Health & Disparities Health Policy Healthcare Innovation Medical Humanities Patient Safety & Quality Improvement Scientific Discovery Doctoring Course Evidence-Based Medicine Interprofessional Education DEIAJ Curriculum Language Opportunities Curriculum Diagrams Grading & Assessments Guideline Budget Loans & Eligibility Financial Aid Application Timeline Scholarships & Grants Documents & Forms Tips & Links Tuition Refund Policies Consumer Information Disbursement & Repayment MD Emergency Student Aid Fund MD Travel Grant Child Care Subsidy Residency Interviewing Loans and Resources Short-Term University Loan Contact the Office of Financial Aid Profiles & Demographics Culinary Connections Students with Disabilities Arts & Humanities Diversity & Health Equity Dual Degrees More Possibilities Commencement Available PhD Programs Academic & Social Events MSTP Fellows Application Process Application Requirements MD | PhD Curriculum Undergrad Summer Program Contact the MD | PhD Program Bioinformatics Biological Chemistry Cancer Biology Cell & Developmental Biology Cellular & Molecular Biology Genetics and Genomics Health Infrastructures & Learning Systems Microbiology & Immunology Molecular, Cellular & Developmental Biology Molecular & Cellular Pathology Molecular & Integrative Physiology Neuroscience Pharmacology Recruitment Events Interview Weekends Certificates & Dual Degrees Quantitative & Computational Biology Emphasis Training Grants Facilities & Resources Stipend & Benefits Professional Development Finding a Position Funding Your Postdoc Hiring Process Postdoc Preview International Postdocs ACGME Fellowships Non-Accredited Fellowships Postdoctoral Physician Scientist Training Salary & Benefits Prerequisites Visiting Residents & Fellows Application Overview & Requirements Tuition & Fees Timeline & Curriculum Information Sessions Program Details Undergrad Summer Research First Days Survival Guide Health Services Mental Health Health, Spirituality & Religion Program For Partners & Families Things to Do in Ann Arbor Getting Around Graduate Medical Education Office of Continuing Medical Education Office of Faculty Affairs & Faculty Development Office of Graduate & Postdoctoral Studies Physician Scientist Education & Training Office of Medical Student Education Points of Blue Diversity, Equity & Inclusion Department Outings PhD Program Accelerated MS Program Dual Degree Program Training & Curriculum BIDS Training Program Proteogenomics Training Program Student Organizations AI & Machine Learning Applications to Complex Genetic Diseases 4D Nucleome Genomics, Gene Regulation & Epigenomics Multi-“omics” Integrative Bioinformatics Protein Structure, Proteomics & Alternative Splicing Systems Biology & Networks Analysis Translational Bioinformatics, Drug Discovery & Pharmacogenomics Software & Bioinformatics Tools The Bioinformatics PhD | MS Dual Degree Program is designed for PhD or Master’s students who wish to pursue a dual Master’s degree in Bioinformatics. How to Apply Diversity Information for Applicants Application Materials Frequently Asked Questions PhD students who wish to pursue a dual Master’s degree in Bioinformatics must apply by August 1 directly to the Bioinformatics Program through the Rackham Graduate School . List the upcoming Fall term as your proposed term of enrollment.   Students who are interested in obtaining a Bioinformatics Master’s degree, while pursuing a PhD are strongly encouraged to consult with Master's Program Director, Dr. Alla Karnovsky before applying for the program.   Interested students should consult with Dr. Alla Karnovsky before enrolling in classes, as applicants with limited computer programming may be required to take preparatory courses in their first year. Grades obtained in these first-year bioinformatics courses will be considered during the evaluation of applicants for suitability for the MS Program.   For PhD students, please note that in addition to the course requirements students must have bioinformatics-related content in their final dissertation. They are also required to have at least one DCMB faculty (primary or joint) on their dissertation committee, who will approve of the bioinformatics-related portion of the dissertation. Dual degree PhD/MS students will have their MS degree conferred in their final term, at the same time as their PhD degree.   If a PhD student applies after August 1 of their first year, a written justification of why the student waited before applying is required. Applications from candidate-level PhD students are discouraged, as the ability to take additional classes is limited for candidates.   The application deadline is August 1. If a PhD student applies after August 1 of their first year, a written justification of why the student waited before applying is required. Applications from candidate-level PhD students are discouraged, as the ability to take additional classes is limited for candidates. The Bioinformatics Graduate Program encourages applications from traditionally underrepresented minorities, students with disabilities, and those from disadvantaged backgrounds. There are funding opportunities and resources both from the program and other campus units to contribute to students' overall well-being while pursuing studies. Several resources available to students can be found on the Rackham Graduate School Diversity, Equity, and Inclusion website . In addition, DCMB’s faculty members participate at events around the country, such as the Annual Biomedical Research Conference for Minority Students ( ABRCMS ). Diversity is a key component of excellence, especially for solving the complex biomedical challenges that our field of computational medicine and bioinformatics faces. We believe that all people—regardless of background, race, religion, sexual/gender orientation, age or disability—deserve an equitable opportunity to pursue the education and career of their choice. All application materials are due by the deadline and should be submitted electronically when possible. Please note that applications submitted early will not be reviewed prior to the deadline.   The Bioinformatics Program requires a minimum GPA of 3.2.   Submit your dual admission application via the Rackham website:  https://rackham.umich.edu/admissions/current-and-former-rackham-students/#dual-admission   The application fee is $10.   All required materials to be submitted via the website above include:   The  Rackham Pre-approval Form , signed by your home department. **DO not send this to the program. It must be submitted online with your application for Rackham to access.   Statement of Purpose   The Statement of Purpose should be a concise, well-written statement about your academic and research background, your career goals, and specific to the Bioinformatics Program.   Current C.V.   UM transcripts (unofficial are ok)   If beyond your first year of graduate study, a written justification of why the application is delayed. Applicants who have already achieved candidacy are discouraged.   The only materials to be submitted directly to the  [email protected]  mailbox:   1.    Letters of recommendation (1 required)*   A letter from your advisor(s) is required. It can be brief (1 – 2 paragraphs), yet it should attest to your abilities and why pursuing a BIOINF MS degree would be appropriate for your studies.   If any questions, please contact the department at  [email protected] (link sends e-mail) .   We find a new reason to love Ann Arbor nearly every day — year-round outdoor activities, cultural experiences, a growing food scene, and a welcoming, family-friendly atmosphere are just a few that come to mind. Explore all that Ann Arbor and our surrounding communities have to offer.  Our Master students are largely self-funded. You may apply for teaching or research assistantships, but there is no guarantee. Please note that the Bioinformatics Program offers few positions and priority is given to PhD students. A student may obtain a teaching position (GSI) in another unit. While many Master's students get some funding, rarely is a student fully funded without some type of external award or fellowship. If interested in research assistantships, you need to contact specific faculty for those positions. Having significant programming experience is helpful. Yes. Some students take coursework while working full time. A student is expected to complete all coursework within five years from the date of first enrollment in the program. Bioinformatics consists of a mathematical and/or statistical analysis of a biomedical problem using computation. We define bioinformatics widely and include traditional bioinformatics areas such as for examples, systems biology, genomics, proteomics, plus statistical and evolutionary genetics, clinical informatics, and protein modeling. As an interdisciplinary field, Bioinformatics attracts graduate students from mathematics, statistics, physics, computer science, biomedical engineering, chemistry, biochemistry and biology. Most incoming students have both a major in one and a minor in another discipline. In recent years students have entered with undergraduate training in bioinformatics or computational biology. No. A thesis option is not available. Students are required to complete a research component (see above) and to publish that work as a scientific article in venues such as conferences or journals. Such publications should be of great benefit to students. We transform lives through bold discovery, compassionate care and innovative education. Find a Doctor Conditions & Treatments Patient & Visitor Guide Patient Portal Clinical Trials Research Labs Research Centers Cores and Resources Programs & Admissions Our Community Departments, Centers & Offices About the Medical School Global Footer Secondary Navigation Get the Reddit app ## A subreddit to discuss the intersection of computers and biology. ------ A subreddit dedicated to bioinformatics, computational genomics and systems biology. PhD-position in bioinformatics / computational biology PhD-position in bioinformatics / computational biology (75% E13) at Ruhr-University Bochum The Computational Phenomics research group uses bioinformatics methods to study the aging process. For example, we are assembling genomes of exceptionally long-lived species to identify evolutionary adaptations that enable these species to age slowly and healthily. Furthermore, we are using multi-omics approaches to understand how environmental and social stressors accelerate aging and the development of associated diseases. In this DFG-funded research project you will investigate (epi-)genomic differences causing mole-rats living several times as long as most other rodents, aging healthily and being extremely resistant to cancer. Furthermore, you will elucidate epigenomic changes causing reproductive mole-rats to age significantly slower than non-reproductive ones. The results shall be published in peer-reviewed journals. ~Your tasks:~ Evaluation of extensive sequencing data sets (WGBS, RRBS, ATAC, RNA-seq) Interpretation of bioinformatic analyses in the context of aging research Preparation of results for publications ~Your Profile~ Master’s degree in bioinformatics / computational biology or a related field, e.g., life sciences, informatics or mathematics Programming skills and ideally Linux command line experience High level of motivation, creativity, self-responsibility and self-organization We are looking forward to receiving your application with the specification as soon as possible, send by e-mail to the following address: [email protected] . Following Dobbs, PRESTO Pregnancy Planners Reduced Engagement with Fertility App Facing Our History on Juneteenth Phd student presents research at puerto rican conference on public health .. Yareliz Diaz. Photo: Megan Jones PhD Student Presents Research at Puerto Rican Conference on Public Health Yareliz Diaz , a PhD student in health services and policy research, joined Carlos Rodriguez-Diaz , chair and professor of community health sciences, on a special panel and Diaz presented work related to her dissertation on the mental health of Puerto Rican migrants to the mainland US after Hurricane Maria. Megan jones. Growing up, Yareliz Diaz always spoke Spanish at home and English at school. Her mother, who immigrated to Boston from Puerto Rico as a teenager, banned Diaz and her sister from speaking English in her house—a rule she enforces to this day, Diaz says. It was not until her undergrad at Tufts that Diaz discovered her mother even speaks English. “I was appalled,” she jokes. When she was younger, her mother sometimes asked her to make phone calls on her behalf, claiming she could not speak English. Diaz consequently became adept at translating between the two languages. Today, as a PhD student at the School of Public Health researching the mental health of Puerto Rican migrants, Diaz forgives her mother for her deception. Her bilingual upbringing empowered her to embrace her Puerto Rican heritage, she says. “Even though I was not raised on the island, my mom has tried to make sure that we have kept in close touch with our culture and because of that I have always felt a deep connection to Puerto Rico.” Diaz enjoys eating traditional Puerto Rican dishes on holidays, listening to Puerto Rican music, and following Puerto Rican media. “I have always tried to stay in touch with what is happening so that I can call myself Puerto Rican and actually know what that means,” she says. However, Diaz still felt nervous when Carlos Rodriguez-Diaz , professor and chair of community health sciences, invited her to serve on a special panel and present her ongoing research at the Puerto Rican Conference on Public Health in San Juan in early May. “All my academic training has been in English, [and] I obviously speak Spanish, but academic Spanish and regular Spanish you speak day-to-day are very different, so that was intimidating,” Diaz says. But Rodriguez-Diaz insisted, lending her his full support and sponsoring her attendance. According to Rodriguez-Diaz, who conducts community-based participatory research in Puerto Rico and was born and raised there, the annual conference is the most important of its kind held on the island. He moderated the panel titled “Hacia una salud pública decolonizada en Puerto Rico: Perspectivas desde la diaspora” or “A Decolonized Perspective for Public Health in Puerto Rico: Perspectives from the Diáspora,” on which Diaz served, both a member of the Puerto Rican diaspora and a scholar researching it. Following nearly four centuries under Spanish rule after the arrival of Christopher Columbus in 1493, Puerto Rico became a territory of the United States when it was acquired during the Spanish-American War in 1898. The island’s territorial status means that while Puerto Ricans are U.S. citizens, they do not have congressional representation and cannot vote in presidential elections. Rodriguez-Diaz is interested in the ways this historical and ongoing colonization drives health inequities between Puerto Ricans and the mainland US population. Since coming to SPH last year, he has joined Sarah Lipson in mentoring Diaz as she has pursued related research on the effects of cascading disasters and residential instability on the mental health of Puerto Ricans who migrated to Florida in the wake of Hurricane Maria in 2017. Using survey data collected from focus groups conducted in 2018, Diaz hopes to better understand how the actions and policies of U.S. government agencies responding to the disaster have affected the experiences and, ultimately, the mental health of Puerto Rican migrants and their families. Coincidentally, it was Diaz herself who transcribed and translated the data from Spanish to English back in 2018, well before she had decided on a dissertation topic, before she had even enrolled at SPH. The research team recruited the recent Tufts graduate with degrees in anthropology and community health to ensure the translations were accurate based on her familiarity with Puerto Rican Spanish. It was this work as a translator that solidified Diaz’s intent to pursue advanced studies in public health, she says. “I was hearing directly from the mouths of these people, who had experienced such a horrible, horrific thing, just how hard it was to migrate. And they are technically American, but what does that actually mean? And what is the impact of being American, but not having access to the same resources and not being treated as such when they got here,” says Diaz, who wrote about her intent to study these questions in her application to SPH. Having the opportunity to now analyze the data and sit on the advisory board for the Adelante Boricua (Onward Puerto Rico) Project, the larger study of Hurricane Maria survivors that her dissertation work will contribute to, Diaz feels as though she has come full circle. “It’s almost like it was meant to be,” she says. “There are folks who participated in the study, who are local leaders in the Orlando and Miami areas, and I will have the opportunity to present the work that I am doing and what my findings are to these folks, get feedback from them, and then work with them to craft policy recommendations that will actually be meaningful and not just someone from the tower of academia saying, ‘This is what you should do.’” If her presentation in Puerto Rico was any indication, it is likely Diaz’s work will be well-received. “This was her first professional presentation in Spanish, and she did it flawlessly! [She] did a phenomenal job and had a great discussion with the audience,” says Rodriguez-Diaz. After returning from the conference, Diaz says she is so grateful for his encouragement and support. “It was one of those moments where I felt really validated as a scholar, like all my work is actually really important,” says Diaz of the experience. “I do not always feel that way. There is a lot of imposter syndrome. Academia is not a place for a person like me, because of the stuff that I want to study, being first gen—all these things. But being in that space around other Puerto Rican scholars who care about Puerto Rico as much as I do, who cared about my work, who thought my work was amazing—it was really cool.” Explore Related Topics: Community Health Sciences health policy Hurricane Maria mental health Puerto Rico student news Share this story 0 Comments Add Writer/Editor, School News Megan Jones is the writer and editor focusing on school news at the School of Public Health. Profile Comments & Discussion Boston University moderates comments to facilitate an informed, substantive, civil conversation. Abusive, profane, self-promotional, misleading, incoherent or off-topic comments will be rejected. Moderators are staffed during regular business hours (EST) and can only accept comments written in English. Statistics or facts must include a citation or a link to the citation. Post a comment. Cancel reply Your email address will not be published. Required fields are marked * 221 IMAGES bioinformatics thesis topics bioinformatics thesis topics Bioinformatics Template Overview of topics covered in this thesis. The Venn diagram shows the PhD Theses Bioinformatics Topics VIDEO PhD Programme at IIMB: PhD scholar Sai Dattathrani, Information Systems area What is Bioinformatics PhD Thesis Topics 10 Most Potential Dissertation Topics (Fisheries & Aquaculture) #msc #zoology #adarshalaya#project Latest Bioinformatics Scientist Job #Bioinformatics COMMENTS 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. Frontiers in Bioinformatics Tallulah Andrews. Constanza Cárdenas Carvajal. Irma Martínez-Flores. 4,047 views. 4 articles. 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. Bioinformatics Related Research Topics 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 useful information ... Bioinformatics & Systems Biology Research Areas Students have the option to choose co-mentors to provide bioinformatics and biological expertise or to or work exclusively with one mentor with bioinformatics expertise. Most of the research projects involve bioinformatic data analyses either preceding (hypothesis-generation) or succeeding (hypothesis-testing) an experimental component. PDF Bioinformatics Group 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). PhD Theses 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. PhD in Bioinformatics Data Science 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. 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 ... Theses 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. More information is ... PhD in Bioinformatics » Academics The PhD in Bioinformatics program offers unique interdisciplinary training for graduate students in the science, engineering, medicine, and ethics of twenty-first-century cell biology jointly through the College of Engineering and the Graduate School of Arts & Sciences. The program aims to prepare top researchers for careers in both academia ... Finished PhD theses The following PhD theses were conducted with support and/or supervision of A. Goesmann: Name. Title of thesis. Year. Christopher Schölzel. Engineering complex mathematical models in systems biology with Modelica. using the example of the human cardiovascular system. 2023. Oliver Schwengers. Bioinformatics and computational biology Presentation of the dissertation topic and progress made so far. The actual "exam"/discussion, based on the presentation and on the supplied topics (see below). Bioinformatics and computational biology is an interdisciplinary programme, but each research topic relies on results from computer science/mathematics and biology. Open thesis topics 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. PDF Thesis in Bioinformatics 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 ... Bioinformatics PHD Thesis Topics Bioinformatics Phd Thesis Topics - Free download as PDF File (.pdf), Text File (.txt) or read online for free. Scribd is the world's largest social reading and publishing site. Bioinformatics PhD Research Projects PhD Projects ... Queen Mary University of London Digital Environment Research Institute. A fully funded PhD Studentship is available to work with Professor Francesca Ciccarelli, Lead of the Centre for Cancer Genomics and Computational Biology, Bart's Cancer Institute at Queen Mary University of London. Read more. Program: Bioinformatics Data Science (PhD) 9 credits. Bioinformatics: BINF 644 - Bioinformatics Credit (s): 3. Data Science - System Biology:: Choose one of the following: BINF 694 - Systems Biology I Credit (s): 3. BINF 695 - Computational System Biology Credit (s): 3. or. Systems Biology recommended elective upon approval by dissertation committee and Graduate Program Director. Oxford LibGuides: Bioinformatics: Theses & Dissertations 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. Already digitised UK theses can be downloaded freely as PDF files. Requests can be made to digitise older theses, but there is a cost of ... Research Areas · PhD Degree Program in Biological and Medical Hiten Madhani. Katherine Pollard. Andrej Sali. Matthew Spitzer. Leor Weinberger. Lani Wu. The Biological and Medical Informatics (BMI) Graduate Program focuses on three areas of research: Biological and medical informatics and computational biology Genetics and genomics Systems biology The fields of biological and medical. Phd Thesis : r/bioinformatics Can you write a phd thesis on ngs data analysis and pipeline, if yes, how would you proceed? The pipeline in question will be used in cancer research. I will really appreciate the help! I major in biotech and wet lab side of the field however, im looking forward to do a phd in bioinformatics. Am I overthinking my Master Thesis? : r/bioinformatics If you go the academic route your thesis is going set the groundwork for your PhD so it's important. If not I can say from experience in bioinformatics with a masters degree, if you have an idea of what to do with a fasta for bam file you are qualified. Yes, you are overthinking it if you are going the industry route. 4. BSc and MSc Thesis Subjects of the Bioinformatics Group 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 ... PhD-position in bioinformatics / computational biology : r/PhD Other. PhD-position in bioinformatics / computational biology (75% E13) at Ruhr-University Bochum. The Computational Phenomics research group uses bioinformatics methods to study the aging process. For example, we are assembling genomes of exceptionally long-lived species to identify evolutionary adaptations that enable these species to age ... DCMB PhD The Bioinformatics PhD | MS Dual Degree Program is designed for PhD or Master's students who wish to pursue a dual Master's degree in Bioinformatics. PhD students who wish to pursue a dual Master's degree in Bioinformatics must apply by August 1 directly to the Bioinformatics Program through the Rackham Graduate School. UMSI PhD Candidate Mez Perez earns 2024 NAEd Spencer Dissertation Friday, 06/14/2024. University of Michigan School of Information doctoral candidate Mez Perez has earned a 2024 National Academy of Education (NAEd) Spencer Dissertation Fellowship. The fellowship is awarded to early-career scholars whose projects address critical issues in the history, theory, or practice of formal or informal education at the ... PhD-position in bioinformatics / computational biology academic. PhD-position in bioinformatics / computational biology (75% E13) at Ruhr-University Bochum. The Computational Phenomics research group uses bioinformatics methods to study the aging process. For example, we are assembling genomes of exceptionally long-lived species to identify evolutionary adaptations that enable these species to age ... PhD Student Presents Research at Puerto Rican Conference on Public Yareliz Diaz , a PhD student in health services and policy research, joined Carlos Rodriguez-Diaz , chair and professor of community health sciences, on a special panel and Diaz presented work related to her dissertation on the mental health of Puerto Rican migrants to the mainland US after Hurricane Maria. June 14, 2024. Megan Jones. 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