Topic outline
-
General
-
STATISTICAL PHYSICS OF GENE EXPRESSION (introduction to basic Systems Biology)
LECTURE N. 20 fri may 11th
this is an area of modern biophysics that, to be sharp, originated around 2006, from many
contributions (first of all super-resolution fluorescence microscopy and the use of CCDs)
but with a prominence - for the clarity of their works - of Xie’s group at Harvard University (https://bernstein.harvard.edu). As an introduction to this field of study I suggest that you give a glance to this page: https://bernstein.harvard.edu/research/probing_gene_expr.htm where you will find mention of the basic reference. A lecture by Jeff Gore, which introduces and comments Xie’s contributions can be found in video at:
https://ocw.mit.edu/courses/physics/8-591j-systems-biology-fall-2014/lecture-videos/introduction-to-stochastic-gene-expression/
-introduction to the competitive (chance/constraints) stochasticity in living systems
-digression on deterministic/probabilistic cellular automata
reference to chap. 19 of PBoC which is, in fact, an introduction (à la Rob Phillips) to
integrative, cellular systems biology.
Study materials:
Statistical Mechanics of gene expression (Kondev’s notes from the net)
-birth-death processes (rate equation)
-Uncontrolled transcriptional regulation
-Chemical master equation for p(n.t), which obeys Poisson statistics
Introduction to the reading of N. Friedman et al., linking stochastic Dynamics to Population Distribution: An analytical Framework of Gene expression, PRL,97:2006)
in which a general master equation is derived and analytically solved through Laplace’s transform (leading to a Gamma Distribution), which is also computed numerically, using the Gillespie algorithm.