Course for international guest/part time students

Faculty
Faculty of Science
Organization
TTK Department of Computer Science
Code
bioinf1u0um17gm
Title
Bioinformatics (p)
Usual semester
Autumn
Published semester
2025/26/2
ECTS
3
Language
hu
Learning outcomes
Knowledge: getting familiar with the main notions of bioinformatics Ability: to understand and use bioinformatics Attitude: the need to deepen the applied mathematical knowledge, to gain new applied mathematical skills, to develop competencies. Aspiration to apply the mathematical knowledge for a wide range of problems Autonomy and Responsibility: based on the gained knowledge in bioinformatics, the students are able to decide which tools are the most suitable to solve applied problems
Course content
Gene sequencing techniques. Introduction to metagenomics. Microbial diversity. Assembly techniques and levels. Re-sequencing and de novo sequencing. Hashing. The Burrows-Wheeler transformation. Graph theory methods: Hamilton, Euler and De Bruijn graphs. Distance of series: Hamming and Levenshtein distance. Dynamic programming. Subsequence search: Knuth-Morris-Pratt and Boyer-Moore algorithm. Suffix trees. Sequence alignment: Needleman--Wunsch and Smith--Waterman algorithms. BLAST and its variants. From genes to proteins: gene annotation. Markov models. Introduction to molecular structures. Protein-small molecule docking. Protein-protein docking. Protein interaction networks.
Assessment method
term grade
Bibliography
lecture notes

Programmes of the course

Title (code) Lang. Level Mandatory Year ...
Alkalmazott matematikus MSc - Számítástudomány szakirány (TTK-ALKMAT-SZÁMTUD-NMHU) hu 7
Applied Mathematician (TTK-ALKMAT-NMHU) hu 7 2/2
Erasmus Programme (TTK-ERASMUS-NXXX) en Mandatory
Mathematician (TTK-MATEMAT-NMHU) hu 7 1/2
Mathematician (TTK-MATEMAT-NMEN) en 7 1/2
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