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150202 ||| eng |
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|a 9783319149141
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| 100 |
1 |
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|a Xu, Jinbo
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| 245 |
0 |
0 |
|a Protein Homology Detection Through Alignment of Markov Random Fields
|h Elektronische Ressource
|b Using MRFalign
|c by Jinbo Xu, Sheng Wang, Jianzhu Ma
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| 250 |
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|a 1st ed. 2015
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2015, 2015
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| 300 |
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|a VIII, 51 p. 13 illus., 1 illus. in color
|b online resource
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| 505 |
0 |
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|a Introduction -- Method -- Software -- Experiments and Results -- Conclusion
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| 653 |
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|a Mathematical statistics
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| 653 |
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|a Bioinformatics
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| 653 |
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|a Computer science / Mathematics
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| 653 |
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|a Computational and Systems Biology
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| 653 |
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|a Probability and Statistics in Computer Science
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| 653 |
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|a Biostatistics
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| 653 |
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|a Biometry
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| 700 |
1 |
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|a Wang, Sheng
|e [author]
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| 700 |
1 |
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|a Ma, Jianzhu
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a SpringerBriefs in Computer Science
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-14914-1
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-14914-1?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 570.113
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| 082 |
0 |
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|a 570.285
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| 520 |
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|a 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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