Basic materials are available on the educator's website:
(https://homel.vsb.cz/~vas218/bio)
Selected study materials are published on the e-learning portal (https://www.vsb.cz/e-vyuka/cs/subject/460-4175/02/edison).
Bioinformatics
| Type of study | Follow-up Master |
|---|---|
| Language of instruction | English |
| Code | 460-4175/02 |
| Abbreviation | BI |
| Course title | Bioinformatics |
| Credits | 4 |
| Coordinating department | Department of Computer Science |
| Course coordinator | Ing. Michal Vašinek, Ph.D. |
Subject syllabus
Lectures
- Introduction to concepts in molecular biology
- Sequence similarity and distance measures
- Indexing and search
- Alignment
- Principles of technologies for biological data analysis
- Genome assembly
- Variant detection
- Gene expression
- Analysis of multi-omics and multimodal data
- Applications of artificial intelligence methods in bioinformatics
- Pangenomes and graph-based references
- Algorithms in regulatory genomics and epigenomics
Exercises (Labs)
- Practicing foundational concepts for working with DNA/RNA/proteins
- Implementing similarity measures and applying them
- Implementing an FM-index for indexing reference sequences
- Implementing mapping of DNA sequences to reference sequences
- Getting familiar with outputs from various technologies for biomedical data analysis
- Implementing algorithms for genome assembly
- Implementing a Bayesian model for variant detection
- Processing transcriptomic data
- Building predictive AI models for the analysis of multi-omics and multimodal data
- Building generative AI models for creating synthetic biological data
- Implementing algorithms for mapping DNA sequences to pan-genome graphs
- Introduction to methods for analyzing regulatory regions of DNA
- Introduction to concepts in molecular biology
- Sequence similarity and distance measures
- Indexing and search
- Alignment
- Principles of technologies for biological data analysis
- Genome assembly
- Variant detection
- Gene expression
- Analysis of multi-omics and multimodal data
- Applications of artificial intelligence methods in bioinformatics
- Pangenomes and graph-based references
- Algorithms in regulatory genomics and epigenomics
Exercises (Labs)
- Practicing foundational concepts for working with DNA/RNA/proteins
- Implementing similarity measures and applying them
- Implementing an FM-index for indexing reference sequences
- Implementing mapping of DNA sequences to reference sequences
- Getting familiar with outputs from various technologies for biomedical data analysis
- Implementing algorithms for genome assembly
- Implementing a Bayesian model for variant detection
- Processing transcriptomic data
- Building predictive AI models for the analysis of multi-omics and multimodal data
- Building generative AI models for creating synthetic biological data
- Implementing algorithms for mapping DNA sequences to pan-genome graphs
- Introduction to methods for analyzing regulatory regions of DNA
E-learning
Literature
[1] Phillip Compeau, Pavel Pevzner, Bioinformatics Algorithms 3rd Edition, Active Learning Publishers, 2018
[2] Arthur Lesk, Introduction to Bioinformatics 5th Edition, Oxford Universitz Press, 2019
[3] Susan Holmes and Wolfgang Huber, Modern Statistics for Modern Biology, Cambridge University Press, 2019
[4] Vince Buffalo, Bioinformatics Data Skills, O’Reilly, 2015
[2] Arthur Lesk, Introduction to Bioinformatics 5th Edition, Oxford Universitz Press, 2019
[3] Susan Holmes and Wolfgang Huber, Modern Statistics for Modern Biology, Cambridge University Press, 2019
[4] Vince Buffalo, Bioinformatics Data Skills, O’Reilly, 2015
Advised literature
[1] Shai Ben-David, Artificial Intellgience for Medicine, Academic Press, 2024