Systems Biology: theory and algorithms
Systems biology is the study of the interactions between the components of a biological system, and how these interactions give rise to the function and behavior of that system.
This course gives the basic systems biology algorithmic approaches, in particular in application to analysis of highthroughput omics data.
Major topics covered are:
Functional genomics and highthroughput technologies in biomedicine.
Systems biology approaches: static and dynamic networks, Boolean static networks, Bayesian static and dynamic networks
Autoregulation and multistability in the biological systems:
Modeling genetics and biochemical networks as chemical reactions via ordinary differential equations (ODE): equilibrium points and linearization, nullclines, limit cycles, Hopf bifurcations.
ODE network inference: ODE inference from perturbations.
Biochemical kinetics via Markov process: Markov chains and continuous Markov processes, forward and backward Kolmogorov equations, Gillespie algorithm, exact and approximate simulation strategies.
Bayesian inference and MCMC: Gibbs sampler, the Metropolis-Hasting algorithm
Inference for stochastic kinetic models: inference given complete data, discrete-time observations.
Modeling genetics and biochemical networks via stochastic differential equations (SDE): stochastic time discrete approximations (strong and weak)
auto-regulatory genetic network,
bifurcations in processes with micro RNA regulations,
the lac operon, genetic toggle,
inference of the expression regulation network
mutations and adaptive evolution
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D.Wilkinson Stochastic Modelling for Systems Biology, Chapman & Hall/CRC ,2006
E Klipp, R Herwig, A Kowald, C Wierling, and H Lehrach. Systems Biology in Practice. Wiley-VCH: 2005
Z. Szallasi, J. Stelling, and V.Periwal (eds.) System Modeling in Cellular Biology: From Concepts to Nuts and Bolts, MIT Press: 2006
B Palsson, Systems Biology – Properties of Reconstructed Networks. Cambridge University Press: 2006
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P.Kloeden, E.Platen, H.Schurz. Numerical Solutions of SDE Through Computer Experiments, Springer, 2003
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