FI:PB051 Computation in Bioinformatics - Course Information
PB051 Computational methods in Bioinformatics and Systems Biology
Faculty of InformaticsSpring 2018
- Extent and Intensity
- 1/1. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
- Teacher(s)
- doc. Ing. Matej Lexa, Ph.D. (lecturer)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Mgr. Vojtěch Bystrý, Ph.D. (seminar tutor) - Guaranteed by
- doc. RNDr. Aleš Horák, Ph.D.
Department of Machine Learning and Data Processing – Faculty of Informatics
Supplier department: Department of Machine Learning and Data Processing – Faculty of Informatics - Timetable
- Tue 16:00–17:50 A219
- Prerequisites
- Knowledge of elementary molecular biology and basic problems in bioinformatics and systems biology is expected. Previous undertaking of courses IV107, PA054 and PB050 is welcome, but not required formally.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Applied Informatics (programme FI, B-AP)
- Bioinformatics (programme FI, B-AP)
- Economic Information Systems (programme ESF, B-SI)
- Informatics with another discipline (programme FI, B-BI)
- Informatics with another discipline (programme FI, B-EB)
- Informatics with another discipline (programme FI, B-FY)
- Informatics with another discipline (programme FI, B-GE)
- Informatics with another discipline (programme FI, B-GK)
- Informatics with another discipline (programme FI, B-CH)
- Informatics with another discipline (programme FI, B-IO)
- Informatics with another discipline (programme FI, B-MA)
- Informatics with another discipline (programme FI, B-TV)
- Informatics (programme FI, B-IN)
- Mathematical Informatics (programme FI, B-IN)
- Mathematics with Informatics (programme PřF, N-MA)
- Parallel and Distributed Systems (programme FI, B-IN)
- Computer Graphics and Image Processing (programme FI, B-IN)
- Computer Networks and Communication (programme FI, B-IN)
- Computer Systems and Data Processing (programme FI, B-IN)
- Programmable Technical Structures (programme FI, B-IN)
- Embedded Systems (programme FI, N-IN)
- Service Science, Management and Engineering (programme FI, N-AP)
- Social Informatics (programme FI, B-AP)
- Artificial Intelligence and Natural Language Processing (programme FI, B-IN)
- Course objectives
- At the end of the course students should be able to: select appropriate methods for a given problem; obtain and prepare necessary data; analyse the data (using their own program or publically available solutions)
- Learning outcomes
- At the end of the course students should be able to:
- select appropriate computational methods for a given problem;
- analyse selected types of experimental data;
- apply software tools to selected problems of data processing;
- construct and modify qualitative models of biological networks. - Syllabus
- The course will be divided into two parts, each will cover 1-2 methods:
- Bioinformatics:
- operations on genomes
- using Markov models
- Systems biology:
- static analysis of biological networks; Cytoscape, MAVisto tools
- genetic regulatory networks reconstruction; Genomica, ARACNE tools
- data integration
- Literature
- recommended literature
- KLIPP, Edda. Systems biology in practice : concepts, implementation and application. Weinheim: Wiley-Vch, 2005, xix, 465. ISBN 3527310789. info
- not specified
- ZVELEBIL, Marketa J. and Jeremy O. BAUM. Understanding bioinformatics. New York, N.Y.: Garland Science, 2008, xxiii, 772. ISBN 9780815340249. info
- Systems biology : principles, methods, and concepts. Edited by Andrzej K. Konopka. Boca Raton: CRC Press, 2007, 244 s. ISBN 9780824725204. info
- WILKINSON, Darren James. Stochastic modelling for systems biology. Boca Raton: Chapman & Hall/CRC, 2006, 254 s. ISBN 1584885408. info
- Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
- Teaching methods
- A combination of lectures and practical computer exercises.
- Assessment methods
- Selected evaluated exercises; written exam
- Language of instruction
- Czech
- Further Comments
- Study Materials
The course is taught annually.
- Enrolment Statistics (Spring 2018, recent)
- Permalink: https://is.muni.cz/course/fi/spring2018/PB051