Bioinformatics II 1200-2EN-MON15L

The course focuses on the following selected topics of current bioinformatics:

1) Clustering methods: greedy, K-means, hierarchical
3) Machine learning, deep learning
2) Hidden Markov Models, sequence profiles
4) Protein threading
5) Comparative modelling
6) Geometric hashing and related algorithms for biomacromolecular structure analysis

Type of course

elective monographs

Prerequisites (description)

It's assumed student already possess basic knowledge of bioinformatics, can explain such topics as homology, sequence alignment, phylogenetic trees, etc.

Course coordinators

Dominik Gront

Learning outcomes

Student:
- understands theoretical basis of a bioinformatical method
- can describe its algorithm
- can apply a tool appropriately to a given research problem

Assessment criteria

Oral presentation of a selected research publication relevant to the course. Student must be present on every lecture

Practical placement

N/A

Bibliography

Review articles circulated during the course

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 1200-2EN-MON15L in USOSweb