PA054 Formal Methods in Systems Biology

Faculty of Informatics
Spring 2010
Extent and Intensity
2/0. 2 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
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
Timetable
Fri 14:00–15:50 B411
Prerequisites
The course expects elementary knowledge of formal methods achieved at bachelor level. This is an interdisciplinary course. The course is recommended especially for students of Bioinformatics.
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 18 fields of study the course is directly associated with, display
Course objectives
At the end of this course students should be able to: use computer-scientific and mathematical methods in the modern biological research paradigm of systems biology; understand the systems-level view of a biological system; employ formal methods to modeling and simulation of biological systems; use relevant software tools.
Syllabus
  • Research in Systems Biology: Purpose, Goal, and Methodology.
  • Modeling and simulation: Deterministic vs. non-deterministic models, Continuous vs. discrete models, Models with uncertainty, Approximation and abstraction, Simulation and analysis.
  • Continuous deterministic models: Approximation of non-linear continuous models, Discrete abstraction in terms of finite-state automata.
  • Discrete deterministic models: Boolean networks, Petri nets, Hybrid models.
  • Discrete non-deterministic models: Markov chains, Stochastic Petri nets, Stochastic Pi-Calculus.
  • Model checking: Application in the process of model validation, Properties of in silico models vs. in vivo/in vitro experiments, Model checking tools.
  • Models with uncertainty: Parameter estimation, Applications to Robustness.
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
Teaching methods
Lectures, group projects. Optional homeworks.
Assessment methods
oral exam (50%), semester project (40%)
Language of instruction
English
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2011, Spring 2012, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2010, recent)
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