From Shannon's Axiomatic Approach to a New Sense of Biological Information - a podcast by MCMP Team

Omri Tal (CPNSS/LSE) gives a talk at the MCMP Colloquium (17 April, 2013) titled "From Shannon's Axiomatic Approach to a New Sense of Biological Information". Abstract: Shannon famously remarked that a single concept of information could not satisfactorily account for the numerous possible applications of the general field of communication theory. Recent interest in assessing the ‘population signal’ from genetic samples has mainly focused on empirical results. I employ some basic principles from Shannon’s work on information theory (Shannon 1948) to develop a measure of information for extracting ‘population structure’ from genetic data. This sense of information is somewhat less abstract than entropy or Kolmogorov Complexity and is utility-oriented. Specifically, given a collection of genotypes sampled from known multiple populations I would like to quantify the potential for correct classification of genotypes of unknown origin. Motivated by Shannon's axiomatic approach in deriving a unique information measure for communication, I first identify a set of intuitively justifiable criteria that any such quantitative information measure should satisfy. I will show that standard information-theoretic concepts such as mutual information or relative entropy cannot satisfactorily account for this sense of information, necessitating a decision-theoretic approach.

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