Protein Homology Detection Through Alignment of Markov Random Fields
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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.
![Protein Homology Detection Through Alignment of Markov Random Fields Protein Homology Detection Through Alignment of Markov Random Fields](https://cos.richshop.de/servlet/images/9783319149141.jpg?w=300)
- Autor: Jinbo Xu / Jianzhu Ma / Sheng Wang
- Format: PDF
- DRM: social-drm (ohne Kopierschutz)
- Erscheinungsdatum: 22.01.2015
- Herausgeber: SPRINGER