Analysis of biological sequences and structures

The course focuses on understanding and implementing methods for analysis of biological sequences, beyond pairwise alignment, and for prediction and analysis of RNA and protein structures. Sequence-based methods covers multiple sequence alignment, reconstruction of phylogenetic trees and detection of sequence motifs, use of hidden Markov models in sequence analysis, and gene prediction. Structure-based methods includes predicting secondary structures in RNA and proteins and alignment of RNA and protein structures. The course focuses on the algorithms and methods but also includes practical application of relevant tools and databases.

On completion of the course the student should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student

• Understands and is able to implement methods for aligning a set of biological sequences
• Understands and is able to implement methods for reconstruction of phylogenetic trees
• Understands and is able to implement methods for motif discovery and detection
• Understands and is able to utilize hidden Markov models for analysis of biological sequences
• Understands the main approaches to gene prediction and is able to implement and use selected algorithms for the same
• Understands representations and formats for describing structures of RNA and proteins
• Understands the main approaches for prediction of secondary structures in RNA and proteins and is able to implement and use selected algorithms for the same
• Understands the Bayesian framework and likelihood in biological data analysis

Skills

The student can

• select and utilize appropriate tools on real biological data and to interpret resulting output
• Implement and adapt algorithms for analyzing sequences and predicting and comparing structures

General competence

The student is able to

• work in teams to address biological questions using computational approaches

Full-time

10

Bachelor

Autumn.