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Protein Homology Detection Through Alignment of Markov Random Fields

Using MRFalign

  • Book
  • © 2015

Overview

  • 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
  • Includes supplementary material: sn.pub/extras

Part of the book series: SpringerBriefs in Computer Science (BRIEFSCOMPUTER)

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Table of contents (4 chapters)

Keywords

About this book

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.

Authors and Affiliations

  • Toyota Technological Institute, Chicago, USA

    Jinbo Xu, Sheng Wang, Jianzhu Ma

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