Computational Genomics

Objectives and Outcomes

Understanding and applying the basics of analysis and assembly of genetic sequences. Introduction to
the basics of analysis of genetic activity in healthy and diseased cells through biological microarrays.
Obtaining a full picture of genetic functions, including expression profiles at mRNA and protein levels.
Ability to assemble and analyse genetic sequences, as well as annotations of genes and proteins in the


The course covers the basic sequence alignment algorithms and the basics of biology needed to
understand the genome. The algorithms to be used are: Smith-Waterman, Needleman-Wunsch, BLAST
family of algorithms. Methods for addressing and correcting genome sequencing errors. Distinguishing
genome sequencing errors from repetitive genome regions. Basics of biology: mutations, a single
nucleotide polymorphism, evolutionary distance between genomes of different species. Simulation of
genomes and evolution. Genome function analysis as an important step towards finding new molecules
(drugs) that could target proteins in diseased cells. Gene expression, microarrays, their applications (e.g.
in the identification of genes expressed in different cell types or different cell states), steps in
experiments with microarrays, quantitative interpretation of results, normalisation, analysis of differential
gene expression, basic statistical analysis of results, their visualisation and numerical interpretation, as
well as classification and clustering of data.

Research work

Studying the literature, primarily scientific journals in the field of bioinformatics and computer genomics.