Hidden Markov Models for Bioinformatics

Download or read book Hidden Markov Models for Bioinformatics written by T. Koski and published by Springer Science & Business Media. This book was released on 2001-11-30 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to give a thorough and systematic introduction to probabilistic modeling in bioinformatics. The book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. Questions of parametric inference, selection between model families, and various architectures are treated. Several examples are given of known architectures (e.g., profile HMM) used in genome analysis. Audience: This book will be of interest to advanced undergraduate and graduate students with a fairly limited background in probability theory, but otherwise well trained in mathematics and already familiar with at least some of the techniques of algorithmic sequence analysis.