Hidden Markov Models for Bioinformatics

Gives a thorough and systematic introduction to probabilistic modeling in bioinformatics. This book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. It also gives examples of known architectures (such as, profile HMM) used in genome analysis.