An Information Processing View of Chemical Reaction Networks

Abhishek Behera
Nikhil S Mande
Friday, 15 Apr 2016, 16:00 to 17:00
A-201 (STCS Seminar Room)
One may wonder how do micro-organisms process spatially and temporally extensive information about their environment and respond in a manner that maximizes their fitness? Such statistical processing would have to be carried out via biochemical reaction pathways. So a natural model of computation to answer the above question is chemical reaction networks with appropriate dynamics (given by mass action kinetics or chemical master equation). In this model of computation we will discuss how one may:

1. (previously known result*) compute the maximum likelihood estimators for log-linear models
2. sample from the probability distribution of a graphical model

*"A Scheme for Molecular Computation of Maximum Likelihood Estimators for Log-Linear Models" - Gopalkrishnan (