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.
| Autorius: | Jinbo Xu, Jianzhu Ma, Sheng Wang, |
| Serija: | SpringerBriefs in Computer Science |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2015 |
| Knygos puslapių skaičius: | 60 |
| ISBN-10: | 331914913X |
| ISBN-13: | 9783319149134 |
| Formatas: | Knyga minkštu viršeliu |
| Kalba: | Anglų |
| Žanras: | Computational biology / bioinformatics |
Parašykite atsiliepimą apie „Protein Homology Detection Through Alignment of Markov Random Fields: Using MRFalign“
