Methods in Bioinformatics 2026/27

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Literature

BV: Brejová, Vinař: Metódy v bioinformatike. (preliminary version of lecture notes in Slovak, only several lectures) pdf
DEKM: Durbin, Eddy, Krogh, Mitchison: Biological sequence analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press 1998. Can be studied in the FMFI library under code I-INF-D-21
ZB: Zvelebil, Baum: Understanding Bioinformatics. Taylor & Francis 2008. Can be studied in the FMFI library under code I-INF-Z-2

For each lecture, we list the book chapters best corresponding to the covered material. However, the lecture may differ substantially from the listed chapters which serve as the source of additional information.

Recordings of lectures in Slovak from 2018/19

playlist on youtube

Notes and presentations

L: lecture (everybody), TI: tutorial for computer science/informatics students, TB: tutorial for biology/chemistry/physics students

Sept. 24

L: Introduction, course rules, sequencing and genome assembly

TI: Introduction to biology

TB: Introduction to computer science, UCSC genome browser

Oct. 1

L: Genome assembly 2

TI: Introduction to probability, genome coverage by sequencing reads

TB: Introduction to dynamic programming, introduction to probability

Oct. 8

L: Sequence alignment: Smith-Waterman, Needleman-Wunsch, scoring

TI: Burrows-Wheeler transform

TB: Dynamic programming for sequence alignment, dotplots

Oct. 15

L: Sequence alignment: heuristic alignment (BLAST), statistical significance of alignments, whole genome alignments, multiple alignments

TI: Advanced algorithms for sequence alignment

TB: Programs for sequence alignment, scoring schemes, introduction to projects

Oct. 22

L: Gene finding, hidden Markov models

TI: Fast similarity search, BLAST, MinHash

TB: Hidden Markov models, E-value

Oct. 29

L: Phylogenetic tree reconstruction (parsimony, neighbor joining, models of evolution)

TI: Algorithms for HMM

TB: Substitution models, bootstrap, tree rooting

Nov. 5

L: Comparative genomics, detection of positive and purification selection, comparative gene finding, phylogenetic HMMs

TI: Substitution models

TB: Project proposals, practical phylogenetic trees

Nov. 12

L: Gene expression, differential expression, clustering, transcription factors, sequence motifs

TI: Felsenstein algorithm, algorithms for HMM and phyloHMM

TB: K-means clustering, enrichment, introduction do Uniprot for projects

Nov. 19

L: Protein structure and function

TI: Motif finding by EM and Gibbs sampling

TB: Introduction to context-free grammars, expression data

Nov. 26

L: RNA, secondary structure, Nussinov algorithm, stochastic context-free grammars, RNA family profiles

TI: Examples of biological databases, HMM topology, introduction to context-free grammars