SpringerBriefs in Computer Science: Using MRFalign

Xu, Jinbo; Wang, Sheng; Ma, Jianzhu

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.

Details

Published by: Springer

Publication Date: 2015-03-03

Format: Paperback

ISBN-13: 9783319149134

DOI: 10.1007/978-3-319-14914-1

Dimensions: 235cm x155cm

Pages: 51