By M. Vidyasagar
This booklet explores vital facets of Markov and hidden Markov techniques and the functions of those principles to numerous difficulties in computational biology. The booklet starts off from first rules, in order that no prior wisdom of chance is critical. although, the paintings is rigorous and mathematical, making it invaluable to engineers and mathematicians, even these no longer drawn to organic purposes. a number workouts is supplied, together with drills to familiarize the reader with suggestions and extra complex difficulties that require deep brooding about the idea. organic purposes are taken from post-genomic biology, specifically genomics and proteomics.
The issues tested comprise ordinary fabric reminiscent of the Perron-Frobenius theorem, temporary and recurrent states, hitting possibilities and hitting occasions, greatest chance estimation, the Viterbi set of rules, and the Baum-Welch set of rules. The publication comprises discussions of super helpful issues now not often obvious on the uncomplicated point, equivalent to ergodicity of Markov approaches, Markov Chain Monte Carlo (MCMC), info concept, and big deviation conception for either i.i.d and Markov strategies. The e-book additionally offers state of the art awareness thought for hidden Markov versions. between organic purposes, it deals an in-depth examine the BLAST (Basic neighborhood Alignment seek procedure) set of rules, together with a accomplished rationalization of the underlying concept. different functions akin to profile hidden Markov types also are explored.