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Algorithms in Bioinformatics

Course developer

Prior knowledge

InfT5039, Fundamental Algorithms

Course abstract

This course aims are to provide a theoretical background to the algorithms in bioinformatics and develop the computational and analytical understanding and skills necessary for processing biological data.Student gets introduced in most important algorithmic methods used within the field. For the problems considered, algorithms for their solution are studied and analyzed, several of these algorithms students have to implement in a programming language of their choice. Course emphasizes bioinformatics problems that are most important with respect to practical applications - protein and nucleotide sequence and protein structure analysis, although a brief introduction in other subfields of bioinformatics is given. Course also gives a brief introduction in main bioinformatics databases.

Learning outcomes and their assessment

Knowledge:
is able to show the depth or extends knowledge and critical understanding about algorithms and computational models in two and more sequence analysis (the practical works are developed, assessment tests successfully are written);
Skills:
Is able to independly implement the sequence analysis algorithms in a programming language of their choice (the practical works are developed, the sequence alignment software is developed);
Competences
is able to independently realize DNA (RNA) and protein sequence analysis by using a bioinformatics algorithms; to interpret the results and to analyze them (assessment tests successfully are written, the sequence alignment software is developed and presented in practical classes).

Course Content(Calendar)

1.Sequence alignment, databases, data formats, on-line software. [L – 1]
2.Two sequence alignment - graphical methods. [L – 1]
3.Two amino acid sequence linear – global alignment. [L – 1, P – 1h]
4.Two amino acid sequence linear – local alignment. [L – 1, P – 1h]
5.Two amino acid sequence affine – global alignment. [L – 2, P – 2h]
6.Two amino acid sequence affine – local alignment. [L – 2, P – 2h]
7.Two protein acid sequence linear – global alignment. [L – 1, P – 1h]
8.Two protein acid sequence linear – local alignment. [L – 1, P – 1h]
9.Two protein acid sequence affine – global alignment. [L – 2, P – 2h]
10.Two protein acid sequence affine – local alignment. [L – 2, P – 2h]
1st test: Two amino acid and protein sequence alignment. [P – 2h]
11. Multiple sequence alignment[L – 2]
12.Software for multiple sequence alignment. Results interpretation. [L – 2, P – 2h]
13.Phylogenetic tree. Types of phylogenetic tree. [L – 2, P – 2h]
14.Building of phylogenetic tree. [L – 2, P – 2h]
15.Software for phylogenetic tree construction. [L – 2, P – 2h]
2nd test: Multiple sequence alignment and phylogenetic tree. [P – 2h]

Requirements for awarding credit points

The test assignment consists of a test on the theoretical subjects acquired during the study course and a practical task on the course subjects. All practical works and tests should be executed.

Description of the organization and tasks of students’ independent work

The organization of independent work during the semester is independently studying literature, using academic staff member consultations. Homework has been developed and defended. Homework: students’ to implement the sequence analysis algorithms in a programming language of their choice.

Criteria for Evaluating Learning Outcomes

Evaluation (Ia) depends on the semester cumulative assessment: 1st test – 40 points, 2nd test – 40 points and homework – 20 points. Students who have a cumulative assessment of the study course less than 4 or wish to improve it (at least 4) hold the complex test during the session. The test includes practical part (80%) and theory (20%).

Compulsory reading

1. Eidhammer I., Jonassen I., Taylor W. Protein Bioinformatics: An Algorithmic Approch to Sequence and Structure Analysis. London: John Wiley & Sons, 2004. 355 p. [VSK 3 eksemplāri]
2. Tisdall J. D. Beginning Perl for Bioinformatics. Cambridge: O'Reilly & Associates, 2001. 368 p. [VSK 3 eksemplāri]
3. Lesk A. M. Introduction to Bioinformatics. New York: Oxford University press, 2002. 283 p. [VSK 3 eksemplāri]
4. Hoeppner M., Latterner M., Siyan K. Bookshelf. The NCBI Handbook [online]. 2nd edition. Bethesda (MD): National Center for Biotechnology Information, 2013. Pieejams: https://www.ncbi.nlm.nih.gov/books/NBK169440/ [skatīts 04.01.18]

Further reading

Bodenhofer U., Bonatesta E., Horejš-Kainrath C., Hochreiter S. msa: an R package for multiple sequence alignment. Bioinformatics, Volume 31, Issue 24, 2015, p. 3997–3999. Pieejams: https://doi.org/10.1093/bioinformatics/btv494 [skatīts 04.01.18]

Notes

Special course for master study programme “Information Technologies”.