Objectives and outcomes
Familiarising students with the contemporary problems in bioinformatics and the computational methods for
solving them. Students should gain an insight into the most prominent algorithms and their
implementations in the form of widely used open-source tools.
Foundations of cellular mechanisms. Genomes and digital file formats used for storing and manipulating
genetic information. Genome-wide association studies. DNA sequencing technologies. Sequence
assembly algorithms, string overlap graphs and De Bruijn graphs. Sequence alignment algorithms. FM
index. Boyer-Moore, Boyer-Moore-Horspool. Smith-Waterman and Needleman-Wunsch algorithms. Cancer genomics. RNA sequencing and data analysis.
Working with standard digital file formats used for storing and manipulating genetic information (BAM,
BED, FASTA, FASTQ, VCF) in Linux command line and using Python. Implementing the basic versions
of the most common algorithms used in bioinformatics. Using the BWA Aligner tool. Using GATK toolkit
for DNA sequencing data analysis. Using Kalisto tool for RNA sequencing data analysis.