IV118 Formal Methods in System Biology

Faculty of Informatics
Spring 2009
Extent and Intensity
2/0/0. 2 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. David Šafránek, Ph.D. (lecturer)
Guaranteed by
prof. Ing. Václav Přenosil, CSc.
Department of Machine Learning and Data Processing – Faculty of Informatics
Contact Person: doc. Ing. Matej Lexa, Ph.D.
Timetable
Mon 16:00–17:50 B411
Prerequisites
The course expects elementary knowledge of mathematical calculus and formal methods achieved at bachelor level. This is an interdisciplinary course.
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
there are 37 fields of study the course is directly associated with, display
Course objectives
This is a course for master students focused on application of formal methods to system-level study of living organisms in terms of in silico models. The course refines the knowledge presented in IV117 Introduction to Systems Biology. The main goal is to offer students an opportunity to get knowledge necessary for efficient application of computer-scientific and mathematical skills in the applied research of Systems Biology. In the theoretical part, main principles of formal modeling and analysis of living organism functionality are explained. In the practical part, a choice of software tools is demonstrated, including the tools developed at Faculty of Informatics. Requirements for successful finishing of the course include ability to choose and apply suitable tools to solve a given biological problem.
Syllabus
  • 1.Research in Systems Biology: Purpose, Goal, and Methodology
  • 2.Modeling of mechanisms which control living organism functionality - Deterministic vs. non-deterministic models - Continuous vs. discrete model - Models with uncertainty - Approximation and abstraction - Simulation and analysis of models
  • 3.Continuous deterministic models - Approximation of non-linear continuous models - Discrete abstraction to finite-state automata - Examples of models
  • 4.Continuous non-nedeterministic models - Langevin equations
  • 5.Discrete deterministic models - Boolean networks - Petri nets - Hybrid models - Examples of models
  • 6.Discrete non-deterministic models - Markov chains - Stochastic Petri nets - Stochastic Pi-Calculus - Examples of models
  • 7.Simulation analysis of in silico models - Gillespi method - Simulation tools - Case studies
  • 8.Model checking and its application to analysis of in silico models - Application in the process of model validation - Properties of in silico models vs. in vivo/in vitro experiments - Model checking tools - Examples of use
  • 9.Models with uncertainty and their use for reconstruction of living organisms - Parameter estimation - Example of use
Literature
  • ALON, Uri. An Introduction to Systems Biology: Design Principles of Biological Circuits. Chapman & Hall/Crc, 2006. info
  • Computational modeling of genetic and biochemical networks. Edited by James M. Bower - Hamid Bolouri. Cambridge: Bradford Book, 2001, xx, 336. ISBN 0262524236. info
  • YEARGERS, Edward K., Ronald W. SHONKWILER and James V. HEROD. An introduction to the mathematics of biology : with computer algebra models. Boston: Birkhäuser, 1996, x, 417 s. ISBN 0-8176-3809-1. info
  • GUTFREUND, H. Kinetics for the life sciences : receptors, transmitters and catalysts. 1st pub. Cambridge: Cambridge University Press, 1995, xi, 346. ISBN 052148586X. info
Assessment methods
The course is finished in terms of a written exam.
Language of instruction
Czech
Further Comments
The course is taught annually.
  • Enrolment Statistics (recent)
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