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Protein Homology Detection Through Alignment of Markov Random Fields = Using MRFalign /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Protein Homology Detection Through Alignment of Markov Random Fields/ by Jinbo Xu, Sheng Wang, Jianzhu Ma.
其他題名:	Using MRFalign /
作者:	Xu, Jinbo.
其他作者:	Wang, Sheng.
面頁冊數:	VIII, 51 p. 13 illus., 1 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Bioinformatics. -
電子資源:	https://doi.org/10.1007/978-3-319-14914-1
ISBN:	9783319149141

Protein Homology Detection Through Alignment of Markov Random Fields = Using MRFalign /
Xu, Jinbo.

Protein Homology Detection Through Alignment of Markov Random FieldsUsing MRFalign /[electronic resource] :by Jinbo Xu, Sheng Wang, Jianzhu Ma. - 1st ed. 2015. - VIII, 51 p. 13 illus., 1 illus. in color.online resource. - SpringerBriefs in Computer Science,2191-5768. - SpringerBriefs in Computer Science,.

Introduction -- Method -- Software -- Experiments and Results -- Conclusion.

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.

ISBN: 9783319149141

Standard No.: 10.1007/978-3-319-14914-1doiSubjects--Topical Terms:

583857
Bioinformatics.

LC Class. No.: QH324.2-324.25

Dewey Class. No.: 570.285

Protein Homology Detection Through Alignment of Markov Random Fields = Using MRFalign /
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