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

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

Computational genomics combines computer science, statistics, and biology to analyze and interpret large-scale genomic data. It involves the development and application of computational algorithms, tools, and techniques to understand the structure, function, and evolution of genomes.

Structural bioinformatics

Structural bioinformatics is the study of the three-dimensional structure of biological molecules and their interactions. It involves the use of computational tools and techniques to predict and analyze the structures of proteins, nucleic acids, and other macromolecules, and to understand how they interact with each other and with small molecules.

Computational proteomics

Computational proteomics analyzes and interprets often large-scale proteomic data using computational methods. It focuses on proteins, their structure, function, and interactions within biological systems. It involves protein identification, quantification, post-translational modifications analysis, and protein-protein interaction networks. It provides insights into cellular processes, and disease mechanisms.


Phylogenetics is the study of the evolutionary relationships between different species or groups of organisms. It involves the use of computational tools and techniques to analyze molecular data, such as DNA sequences, to reconstruct evolutionary trees and infer the relationships between different species.

Population genetics

Population genetics is the study of the genetic variation within and between populations of organisms. It involves the use of statistical methods and computational tools to analyze genetic data, such as DNA sequences and SNP data, to understand the patterns of genetic variation and the evolutionary forces that shape them.

Systems biology

Systems biology combines biology, mathematics, and computer science to understand the complex behavior of biological systems at the molecular, cellular, and organismal levels. It involves the use of computational models and simulations to study the interactions between different components of biological systems, and to predict the behavior of these systems under different conditions.

Neuroinformatics/Computational neuroscience

Neuroinformatics is the application of computational methods and tools to study the structure and function of the nervous system. It involves the development of databases, algorithms, and models to analyze and interpret large-scale data from a variety of sources, including neuroimaging, electrophysiology, and behavioral experiments.


Bioimaging is the use of imaging techniques, such as microscopy and MRI, to visualize biological structures and processes. It involves the development of computational algorithms and tools to analyze and interpret the images, and to extract quantitative information about the biological systems being studied.

Bioactive molecule discovery/Computational drug discovery

Bioactive molecule discovery refers to the process of identifying and designing molecules (drugs in case of computational drug discovery) with potential therapeutic or biological activity. Techniques such as molecular modeling, virtual screening, and other computational approaches are utilized to predict the interaction between molecules and target proteins or biological pathways. These methods help assess binding affinity, pharmacological properties, and optimize the structure and properties of potential bioactive molecules to enhance their efficacy and safety.

Molecular modeling

Molecular modeling is a technique that relies on computer methods to study the behavior of molecules and their interactions. Using advanced computational techniques, the behavior of three-dimensional models of molecules can be simulated under different conditions allowing to model the behavior of molecules in complex systems. Molecular modeling has become an important tool in structural bioinformatics, drug discovery, or materials design, due to its ability to provide insights into the molecules’ behavior which is difficult or impossible to obtain experimentally.

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.


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:

  1. Given the dynamics of the field, specific topics would need to be updated frequently.
  2. 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:

  1. Presentation of the dissertation topic and progress made so far.
  2. 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

  1. A general description with a definition of the dissertation topic
  2. A list of accomplishments and a plan of work
  3. 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.


  • 03/2024We have been holding the second run of the bioinformatics academia-industry meetup called Bioinformatics - a bridge between industry and academia.
  • 02/2024As 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.
  • 01/2024During 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.
  • 05/2023Programme materials available on the website
  • 02/2023We have been holding a bioinformatics academia-industry meetup called Bioinformatics - a bridge between industry and academia.
  • 01/2023Accreditation application approved by the Faculty of Mathematics and Physics dean's collegium
  • 12/2022Accreditation application finished
  • 11/2022Subject area board established


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