Introduction to bioinformatics 2

obligatory courses

The course focuses on bioinformatics techniques used to study proteins from an evolutionary perspective. It will cover essential tools (Linux, Python) and methods for protein structure and sequence analysis. The goal of the course is to provide practical skills for performing both high-throughput analyses aimed at the diversity and evolution of entire protein families, as well as in-depth analyses of individual proteins, particularly in the context of experimental research. The course is designed for individuals interested in expanding their knowledge of programming and biological data analysis.

The following topics will be covered in this class:

• Python programming basics, libraries (Pandas, Seaborn, Numpy, BioPython), visualization and processing of large amounts of data

• Homology, analogy and coevolution in the context of protein sequences and structures, concepts of protein families and domains and how to classify them

• Sequence and structure databases (AFDB, ECOD, UniProt), accessing databases from Python scripts

• Sequence methods (HHsuite, HMMER, MMseqs2, CCmpred), homology detection, function determination and protein classification

• Structural methods (AlphaFold, FoldSeek, PyMol), modelling of oligomers, protein-protein interactions and fibrous structures

• Protein language models, embeddings and tools based on them, such as pLM-BLAST. tSNE/UMAP visualization techniques

• Carry out your own experiment based on the knowledge gained. Design from a pool of available designs or self-invented

- Branden, C., & Tooze, J. (1999). Introduction to protein structure (2nd ed.). Garland Science.

- Cheng, H., Schaeffer, R. D., Liao, Y., Kinch, L. N., Pei, J., et al. (2014).

ECOD: An evolutionary classification of protein domains. PLOS Computational Biology, 10(12), e1003926.

Advanced understanding and application of different bioinformatics methods and tools available as standalone programs suits or as a web services.

• Laboratories: Work in small groups to complete a project and present the results.

• Lecture: A passing grade in the laboratories allows you to take the exam (test), which covers theoretical knowledge (lecture) and practical skills (labs).