Protein Homology Detection Through Alignment of Markov Random Fields
Using MRFalign
Nonfiction, Computers, Advanced Computing, Computer Science, Application Software, Science & Nature, Science
| 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.
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.
