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Protein Homology Detection Through Alignment of Markov Random Fields
Wang, Sheng; Xu, Jinbo; Ma, Jianzhu
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Description for Protein Homology Detection Through Alignment of Markov Random Fields
Paperback. Series: SpringerBriefs in Computer Science. Num Pages: 59 pages, 12 black & white illustrations, 1 colour illustrations, 17 black & white tables, biography. BIC Classification: PBT; PSA; PSD; UYAM. Category: (G) General (US: Trade). Dimension: 235 x 155 x 3. Weight in Grams: 135.
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.
Product Details
Format
Paperback
Publication date
2014
Publisher
Springer International Publishing AG Switzerland
Number of pages
59
Condition
New
Series
SpringerBriefs in Computer Science
Number of Pages
51
Place of Publication
Cham, Switzerland
ISBN
9783319149134
SKU
V9783319149134
Shipping Time
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Ref
99-15
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