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Algorithms in Bioinformatics

Course developer

Prior knowledge

InfT5039, Fundamental Algorithms

Replaced course

Biol6012 [GBIO6012] Algorithms in Bioinformatics II

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. Students are introduced in most important two and many nucleotide and protein sequence algorithms, and phylogenetic tree construction algorithms. 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. The course also gives a brief introduction to the 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, test with calculations successfully is written);
Skills:
Is able to independently 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 realise DNA (RNA) and protein sequence analysis by using a bioinformatics algorithms; to interpret the results and to analyse them (test with calculations successfully is written, the sequence alignment software is developed and presented).

Course Content(Calendar)

1. Sequence alignment, databases, data formats, on-line software. [L – 1]
2. Introduction to two and multiple sequence alignment. [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 and local alignment. [L – 1, P – 1h]
6. Two-protein sequence linear – global alignment. [L – 1, P – 1h]
7. Two-protein sequence linear – local alignment. [L – 1, P – 1h]
8. Two-protein sequence affine – global and local alignment. [L – 1, P – 1h]
9. Multiple sequence alignment[L – 1]
10. Software for multiple sequence alignment. Results interpretation. [L – 1, P – 1h]
11. Phylogenetic tree. Types of phylogenetic tree. [L – 1, P – 1h]
12. Phylogenetic tree construction. [L – 1, P – 1h]
13. Software for phylogenetic tree construction. [P – 1h]
Test with calculations: Two and multiple sequence alignment and phylogenetic tree. [P – 2h]

Requirements for awarding credit points

Test. 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 depends on the semester cumulative assessment: test with calculations – 70 points, homework – 30 points. A student must collect 50 points for a positive assessment of the study course.

Compulsory reading

1.Gagniuc, P. A. (2022). Jupiter Bioinformatics (V1). Theory and Implementation. John Wiley & Sons, Hoboken, NJ, USA, 2021, ISBN: 9781119697961) https://doi.org/10.6084/M9.FIGSHARE.192092
2. 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 11.12.2023.]
3. 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]
4. Lesk A. M. Introduction to Bioinformatics. New York: Oxford University press, 2002. 283 p. [VSK 3 eksemplāri]

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 11.12.2023.]

Notes

Study course for master study programme “Information Technologies”.