Course detail

System Biology

FEKT-MPC-SYSAcad. year: 2018/2019

Not applicable.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

prof. Ing. Valentine Provazník, Ph.D.

Department

Department of Biomedical Engineering (UBMI)

Learning outcomes of the course unit

Students will be able to:
- mathematically describe the main components of gene expression
- mathematically describe the main components of signal transduction pathways
- mathematically describe the main components of neuronal pathways
- analyze network graphs using network motifs
- name the main network motifs of transcription, signal-transduction and neuronal-system networks
- explain principles of the main network motifs of transcription, signal-transduction and neuronal-system networks
- describe experimental mathods in systems biology

Prerequisites

Students enrolled in this subject should be able to describe cellular systems, its main components regarding structure and function; analyze systems of ordinary differential equations and apply basic knowledge of probability distribution and combinatorics. In general, knowledge on the Bachelor's degree level is requested.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Techning methods include lectures and computer laboratories. Course is taking advantage of e-learning (Moodle) system.

Assesment methods and criteria linked to learning outcomes

upto 30 points from laboratories
upto 78 points from examination.
Examination has a written form.

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The aim of the subject is to provide students with basic knowledge of computational models in cellular biology and way of their use, knowledge of analysis methods applied to models in systems biology.

Specification of controlled education, way of implementation and compensation for absences

Laboratory tutorials are compulsory, properly justified absence can be compensated based on agreement of the tutor (usually in the last semester week).

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Alon, U: An Introduction to Systems Biology, Design Principles of Biological Circuits. CRC, 2007, ISBN: 1-58488-642-0 (EN)
Konopka, A.K. Systems Biology: Principles, Methods, and Concepts. CRC, 2006, ISBN: 978-0824725204 (EN)
Rosypal, S. Nový přehled biologie. Scientia, Praha 2003. ISBN 80-7183-268-5 (CS)

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme MPC-BTB Master's 1 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

prof. Ing. Valentine Provazník, Ph.D.

Syllabus

1. Introduction to systems biology - from molecular biology of cell to computational models
2. Modeling of biochemical systems - mathematical and computational models to describe processes in living organisms
3. Specific biochemical systems - mathematical modelling of biological and chemical processes in examples
4. Model fitting - design and verification of correct models, comparison to real living systems
5. Analysis of high-throughput data - recent methods used in bioinfnormatics and their implications to systems biology
6. Gene expression models - mathematical modelling of gene expression
7. Stochastic systems and variability - from deterministic to stochastic description of nearly chaotic biochemical processes
8. Network structures, dynamics, and function - networks of models and their use
9. Optimality and evolution - extended dynamic and adaptive models for evolving processes
10. Experimental techniques in molecular biology
11. Linear control systems in modelling
12. Computer modeling tools in practice
13. Systems biology for future

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

prof. Ing. Valentine Provazník, Ph.D.

Syllabus

1. Specific biochemical systems - mathematical modelling of biological and chemical processes in examples
2. Gene expression models - mathematical modelling of gene expression
3. Stochastic systems and variability - from deterministic to stochastic description of nearly chaotic biochemical processes
4. Optimality and evolution - extended dynamic and adaptive models for evolving processes
5. Selected computer modeling tools
6. Individual projects