Algorithms in Bioinformatics II

Total Hours in Course120

Number of hours for lectures16

Number of hours for laboratory classes32

Date of course confirmation18.01.2012

Responsible UnitInstitute of Computer Systems and Data Science

Course developer

prof.

Līga Paura

Dr. agr.

Replaced course

BiolM001 [GBIOM001] Algorithms in Bioinformatics

Course abstract

Student gets introduced in comparatively more advanced problems of bioinformatics and in methods and algorithms for their solution. Emphasized are the areas of bioinformatics, which already now offers solutions that are useful in practice (phylogenetic trees, genomics, applications of machine learning and data mining in bioinformatics etc). Student learns about algorithms for the solution of these problems, and about available programs and databases.

Learning outcomes and their assessment

• Knowledge depth knowledge and critical understanding about algorithms and computational models in two and more sequence analysis, phylogenetic trees, applications of machine learning and data mining in bioinformatics;
• skills to implement the sequence analysis algorithms in a programming language of their choice;
• competence to realize DNA (RNA) and protein sequence analysis by using a bioinformatics algorithms; to interpret the results and to analyze them.

Compulsory reading

1. Eidhammer I., Jonassen I., Taylor W. Protein Bioinformatics, An Algorithmic Approch to Sequence and Structure Analysis. Chichester: John Wiley & Sons, 2004. 355 p.
2. Tisdall J. D. Beginning Perl for Bioinformatics. Beijing, Cambridge: O'Reilly & Associates, 2001. 368 p.
3. Lesk A. M. Introduction to Bioinformatics. New York: Oxford University press, 2002. 283 p.

Atsauksmes