Random Interactions
Practical Applications of Mutual Information: Phylogenetic Trees, Independent Component Analysis, and Network Inferences
by Prof. Peter Grassberger (Juelich Research Centre, Germany)
Thursday, November 8, 2012
from
to
(Asia/Kolkata)
at Colaba Campus ( A304 )
at Colaba Campus ( A304 )
Description |
The mutual information (MI) between X an Y is the amount by which the information (either in Shannon or Kolmogorove sense) needed to specify one is decreased when the other is known. It is non-negative and symmetric, and vanishes only when X and Y are independent, therefore it is a very natural candidate for a universal similarity measure. I will first review the general concepts and practical methods for estimating MI. The I will present three applications: (a) Independent component analysis, illustrated by the problem of disentangling the EEG of a pregnant woman into the one of the mother and the one of the fetus; (b) Classifying "texts", either of natural languages or of DNA. In the latter case, I will discuss MI-based methods to construct phylogenetic trees from mitochondrial DNA; and (c) Attempts to reconstruct gene regulation networks from gene expression data obtained by microarrays. |