Bioinformatics

Study program
second degree

The curriculum is structured in a modular format.

The first semester provides a solid foundation common to all students—regardless of whether the applicant has a background in the natural sciences or computer science. Starting in the second semester, students choose one of three specializations and can also select courses from the other tracks, allowing them to flexibly shape their skill set.

Semester I — Fundamentals

The first semester provides a foundation and builds the skills necessary for further specialized study. The curriculum covers Python programming, working in a Linux environment with version control systems, mathematical and statistical methods used in bioinformatics, and an introduction to biological concepts. All courses combine lectures with practical exercises so that students work with real data and tools from day one.

Semesters 2 and 3 — specializations

Students take courses within their chosen specialization, supplementing them with two elective courses from other tracks each semester:

Nucleic acid bioinformatics

This specialization prepares students to work with next-generation sequencing (NGS) data. The program covers the full cycle of genomic and transcriptomic data analysis—from quality control of raw reads, through mapping and variant detection, to gene expression analysis (RNA-seq) and interpretation of results in diagnostic and research contexts. Graduates are prepared to work in laboratories, genomic centers, and teams focused on personalized oncology or the diagnosis of rare diseases.

Structural bioinformatics and proteomics

This specialization focuses on the structure and function of proteins—a key area for drug design and protein engineering. The program covers protein structure prediction (including deep learning-based approaches such as AlphaFold), molecular docking, virtual screening, molecular dynamics, and computational proteomics. Graduates are prepared to work in the R&D departments of pharmaceutical companies, structural biology teams, and companies offering molecular modeling services.

Applied bioinformatics and technology transfer

This specialization combines technical expertise with business knowledge. The program covers the management of technology and research projects, intellectual property protection, medical device regulations, business models in biotechnology, and the development of bioinformatics products—including software, SaaS platforms, and analytical services. Graduates are prepared for leadership roles such as project manager, product owner, and bioinformatics department manager, as well as for starting their own companies that commercialize bioinformatics solutions.

Semester 4 — Advanced Technologies and Master’s Thesis

The final semester brings together knowledge from all tracks. Students take core courses in cloud computing and Big Data, machine learning and deep learning in bioinformatics, and data analysis process management. The program culminates in a master’s thesis.

Key distinguishing feature: AI in every subject

Artificial intelligence tools are integrated throughout the software, from sequence analysis and protein modeling to the automation of analytical processes. The software treats AI not as an isolated module, but as a natural tool for today’s bioinformaticians.