Course detail
Advanced analysis of large genomic data
FEKT-DBT1Acad. year: 2018/2019
Representation of genomic and proteomic data. Deterministic and probabilistic models of sequence evolution. Methods of construction of large phylogenetic trees. Motifs searching in genomic and proteomic sequences.
Language of instruction
Number of ECTS credits
Mode of study
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
2. Deterministic descriptionof sequences in space.
3. The theory of fractals in the representation of sequences.
4. Deterministic models of sequence evolution.
5. Probabilistic models of sequence evolution.
6. Advanced principles of phylogenetics.
7. Methods of construction of large phylogenetic trees.
8. Quality in phylogenetics.
9. Principles of representation of proteomic data.
10. Advanced encoding of proteomic data.
11. Motif search in genomic and proteomic sequences.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Mandoiu, I. I., Zelikovski, A. Bioinformatics Algorithms. A John Wiley Publishing, 2008.
Snustad, D. P., Simmons, M. J. Genetika. Nakladatelství Masarykovy univerzity, Brno, 2009.
Yang, Z. Computational Molecular Evolution. Oxford University Press, 2006.
Recommended reading
Classification of course in study plans