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Last update: G_M (29.05.2013)
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Last update: G_M (29.05.2013)
The aim of the lecture to interpret some parts of statistics and stochastic processes, typically used in some problems of modern biology. |
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Last update: G_M (29.05.2013)
Taylor, H.M. and Karlin, S. An Introduction to Stochastic Modeling. 3rd Edition, Academic Press, Inc., 1998.
L.J.S. Allen (2003) An Introduction to Stochastic Processes with Applications to Biology. Pearson Prentice Hall.
J.K. Percus (2002) Mathematics of Genome Analysis. Cambridge University Press, New York. |
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Last update: G_M (29.05.2013)
Lecture. |
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Last update: G_M (29.05.2013)
1. Background 1.1 Stochastic processes and statistics. 1.2 Limit theorems (approximation techniques) . 1.3 Survival theory. 1.4 Methods of multivariate analysis. 1.5 Multiple testing theory 2. Show how stochastic models arise naturally in biology. 2.1 Population growth, epidemics, gene regulatory networks, etc. 2.2 Stochastic (bio) chemical kinetic models. 2.3 Survival and cure modeling. 2.4 Statistical analysis of microarrays. |
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Last update: RNDr. Jitka Zichová, Dr. (19.06.2019)
Lebesgue integral, multivariate calculus, linear algebra |