Protein Homology Detection Through Alignment of Markov Random Fields: Using MRFa

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Protein Homology Detection Through Alignment of Markov Random Fields by Jinbo Xu, Sheng Wang, Jianzhu Ma

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.

FORMAT
Paperback LANGUAGE
English CONDITION
Brand New Publisher Description

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.

Back Cover

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.

Table of Contents

Introduction.- Method.- Software.- Experiments and Results.- Conclusion.

Long Description

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.

Feature

Surveys the key topics to aid the reader in quickly learning about this area Presents a novel technique for protein homology search, preparing the reader for future developments Provides an introduction to the software and the web server, enabling the reader to easily make use of the new technique

Details ISBN331914913X ISBN-10 331914913X ISBN-13 9783319149134 Format Paperback Author Jianzhu Ma Short Title PROTEIN HOMOLOGY DETECTION THR Language English Media Book Imprint Springer International Publishing AG Subtitle Using MRFalign Place of Publication Cham Country of Publication Switzerland Edition 2015th Pages 51 DOI 10.1007/978-3-319-14914-1 Translator Irina Leopoldoff Martin Edited by Eduard Nitu Birth 1974 Affiliation Massachusetts Institute of Technology Position journalist Qualifications S. J. Publisher Springer International Publishing AG Edition Description 2015 ed. Series SpringerBriefs in Computer Science Year 2015 Publication Date 2015-03-03 DEWEY 519.2/3 Audience Professional & Vocational Country of Origin NL Product Class Description Computing: General Alternative 9783319149141 Illustrations 1 Illustrations, color; 12 Illustrations, black and white
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