Course detail
Analysis of Biological Sequences
FEKT-MPC-ABSAcad. year: 2024/2025
The course covers the following topics of biological sequence analysis:
- Genetic variation, mutations and population genetics
- Models of DNA, protein and codon sequence evolution
- Methods for construction, quality assessment and interpretation of phylogenetic trees
- Numerical representations and numerical processing of genomic signals
- Methods of annotation, evaluation of stereochemical quality and mutual similarity of tertiary structures of proteins
- Transcription, assembly and quality assessment of sequencing data
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Entry knowledge
Rules for evaluation and completion of the course
up to 60 points from finel oral exam
The exam is oriented to verification of orientation in terms of advanced processing of biological sequences, ability to design methods for sequence analysis, apply operations on sequences.
Computer exercises are obligatory. Excused absence can be substituted.
Aims
The student will be able to:
- describe basic methods of computer processing of symbolic sequences,
- explain characteristics of DNA and protein evolution,
- describe principle of methods for construction and analysis of fylogenetic trees,
- discus advantages and disadvantages of the methods,
- explain principle of numeric conversion of symbolic biological sequences.
Study aids
Prerequisites and corequisites
Basic literature
Durbin, R. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press, 2002. ISBN: 978-0521629713 (EN)
Rosypal, S. Nový přehled biologie. Scientia, Praha 2003. ISBN 80-7183-268-5 (CS)
Srinivasa, K. G. Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications. Springer, 2020. ISBN 978-9811524448 (EN)
Recommended reading
Pevzner, P. A. An Introduction to Bioinformatics Algorithms (Computational Molecular Biology. The MIT Press, 2004. ISBN: 978-0262101066 (EN)
Elearning
Classification of course in study plans
- Programme MPC-BTB Master's 1 year of study, summer semester, compulsory
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. Classic and modern pairwise alignment algorithms.
3. Statistical significance of alignment scores and the interpretation of alignment algorithm's output.
4. Mechanism and the use of dynamic programming.
5. Implementation of Needleman-Wunch and Smith-Waterman algorithms.
6. Multiple alignment and phylogenetic reconstruction.
7. Evolution assumed by different models and algorithms.
8. Likelihood approach to phylogenetic reconstruction.
9. Markov models and hidden Markov models (HMM) in the genomic context.
10. Essential algorithms for making inference on HMM.
11. HMMs to gene finding.
12. Other algorithms in gene-finding.
13. Identify important algorithmic/statistical advances in bioinformatics that address biologically important questions.
Exercise in computer lab
Teacher / Lecturer
Syllabus
- Genetic variability
- Models of DNA evolution
- Models of protein evolution
- Phylogenetic trees Introduction
- Phylogenetic trees - construction
- Evaluation of phylogenetic analysis
- Description of protein structure
- Comparison of protein structures
- Sequencing data entry
- Sequencing data processing
- CNV and methylation analysis
- Numerical and graphical representations
Project
Teacher / Lecturer
Syllabus
Elearning