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010   $a3-319-14914-8
024 7 $a10.1007/978-3-319-14914-1
035   $a(CKB)3710000000342593
035   $a(EBL)1966836
035   $a(SSID)ssj0001424573
035   $a(PQKBManifestationID)11891915
035   $a(PQKBTitleCode)TC0001424573
035   $a(PQKBWorkID)11367548
035   $a(PQKB)10906036
035   $a(DE-He213)978-3-319-14914-1
035   $a(MiAaPQ)EBC1966836
035   $a(PPN)183518187
035   $a(EXLCZ)993710000000342593
100   $a20150122d2015      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aProtein Homology Detection Through Alignment of Markov Random Fields $eUsing MRFalign /$fby Jinbo Xu, Sheng Wang, Jianzhu Ma
205   $a1st ed. 2015.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015.
215   $a1 online resource (59 p.)
225 1 $aSpringerBriefs in Computer Science,$x2191-5768
300   $aDescription based upon print version of record.
311 08$a3-319-14913-X 
320   $aIncludes bibliographical references.
327   $aIntroduction -- Method -- Software -- Experiments and Results -- Conclusion.
330   $aThis work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications. The text first surveys a few popular homology detection methods, such as Position-Specific Scoring Matrix (PSSM) and Hidden Markov Model (HMM) based methods, and then describes a novel Markov Random Fields (MRF) based method developed by the authors. MRF-based methods are much more sensitive than HMM- and PSSM-based methods for remote homolog detection and fold recognition, as MRFs can model long-range residue-residue interaction. The text also describes the installation, usage and result interpretation of programs implementing the MRF-based method.
410  0$aSpringerBriefs in Computer Science,$x2191-5768
606   $aBioinformatics
606   $aMathematical statistics
606   $aStatistics
606   $aComputational Biology/Bioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/I23050
606   $aProbability and Statistics in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17036
606   $aBioinformatics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15001
606   $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030
615  0$aBioinformatics.
615  0$aMathematical statistics.
615  0$aStatistics.
615 14$aComputational Biology/Bioinformatics.
615 24$aProbability and Statistics in Computer Science.
615 24$aBioinformatics.
615 24$aStatistics for Life Sciences, Medicine, Health Sciences.
676   $a004
676   $a005.55
676   $a519.5
676   $a570285
700   $aHo?$b Ku?m-p'a$4aut$4http://id.loc.gov/vocabulary/relators/aut$01868555
702   $aWang$b Sheng$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aMa$b Jianzhu$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910299230003321
996   $aProtein Homology Detection Through Alignment of Markov Random Fields$94476519
997   $aUNINA