Protein Homology Detection Through Alignment of Markov Random Fields Using MRFalign /
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) b...
Κύριοι συγγραφείς: | , , |
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Συγγραφή απο Οργανισμό/Αρχή: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Cham :
Springer International Publishing : Imprint: Springer,
2015.
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Σειρά: | SpringerBriefs in Computer Science,
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Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Περίληψη: | 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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Φυσική περιγραφή: | VIII, 51 p. 13 illus., 1 illus. in color. online resource. |
ISBN: | 9783319149141 |
ISSN: | 2191-5768 |