Protein Homology Detection Through Alignment of Markov Random Fields

Using MRFalign

Nonfiction, Computers, Advanced Computing, Computer Science, Application Software, Science & Nature, Science
Cover of the book Protein Homology Detection Through Alignment of Markov Random Fields by Jinbo Xu, Sheng Wang, Jianzhu Ma, Springer International Publishing
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Author: Jinbo Xu, Sheng Wang, Jianzhu Ma ISBN: 9783319149141
Publisher: Springer International Publishing Publication: January 22, 2015
Imprint: Springer Language: English
Author: Jinbo Xu, Sheng Wang, Jianzhu Ma
ISBN: 9783319149141
Publisher: Springer International Publishing
Publication: January 22, 2015
Imprint: Springer
Language: English

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.

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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.

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