Protein Homology Detection Through Alignment of Markov Random Fields - Using MRFalign (Paperback, 2015 ed.)

This work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications. The text first surveys a few popular homology detection methods, such as Position-Specific Scoring Matrix (PSSM) and Hidden Markov Model (HMM) based methods, and then describes a novel Markov Random Fields (MRF) based method developed by the authors. MRF-based methods are much more sensitive than HMM- and PSSM-based methods for remote homolog detection and fold recognition, as MRFs can model long-range residue-residue interaction. The text also describes the installation, usage and result interpretation of programs implementing the MRF-based method.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Computer Science
Release date:	March 2015
First published:	2014
Authors:	Jinbo Xu • Sheng Wang • Jianzhu Ma
Dimensions:	235 x 155 x 3mm (L x W x T)
Format:	Paperback
Pages:	51
Edition:	2015 ed.
ISBN-13:	978-3-319-14913-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Science & Mathematics > Biology, life sciences > Molecular biology Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General
LSN:	3-319-14913-X
Barcode:	9783319149134

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