ITP OpenIR  > SCI期刊论文
Faraggi, E; Zhou, YQ; Kloczkowski, A; Faraggi, E (reprint author), Indiana Univ Sch Med, Dept Biochem & Mol Biol, Indianapolis, IN 46202 USA.
Accurate single-sequence prediction of solvent accessible surface area using local and global features
Source PublicationPROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
Language英语
KeywordProtein Secondary Structure Backbone Torsion Angles Real-value Prediction Regression
AbstractWe present a new approach for predicting the Accessible Surface Area (ASA) using a General Neural Network (GENN). The novelty of the new approach lies in not using residue mutation profiles generated by multiple sequence alignments as descriptive inputs. Instead we use solely sequential window information and global features such as single-residue and two-residue compositions of the chain. The resulting predictor is both highly more efficient than sequence alignment-based predictors and of comparable accuracy to them. Introduction of the global inputs significantly helps achieve this comparable accuracy. The predictor, termed ASAquick, is tested on predicting the ASA of globular proteins and found to perform similarly well for so-called easy and hard cases indicating generalizability and possible usability for de-novo protein structure prediction. The source code and a Linux executables for GENN and ASAquick are available from Research and Information Systems at , from the SPARKS Lab at , and from the Battelle Center for Mathematical Medicine at . Proteins 2014; 82:3170-3176. (c) 2014 Wiley Periodicals, Inc.
2014
ISSN0887-3585
Volume82Issue:11Pages:3170-3176
Subject AreaPhysics
DOI10.1002/prot.24682
Indexed BySCI
Funding OrganizationNational Institutes of Health (NIH) [R01GM072014, R01GM073095, R01GM085003]; National Science Foundation (NSF) [MCB 1071785]; National Health and Medical Research Council [1059775] ; National Institutes of Health (NIH) [R01GM072014, R01GM073095, R01GM085003]; National Science Foundation (NSF) [MCB 1071785]; National Health and Medical Research Council [1059775] ; National Institutes of Health (NIH) [R01GM072014, R01GM073095, R01GM085003]; National Science Foundation (NSF) [MCB 1071785]; National Health and Medical Research Council [1059775] ; National Institutes of Health (NIH) [R01GM072014, R01GM073095, R01GM085003]; National Science Foundation (NSF) [MCB 1071785]; National Health and Medical Research Council [1059775]
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Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itp.ac.cn/handle/311006/15593
CollectionSCI期刊论文
Corresponding AuthorFaraggi, E (reprint author), Indiana Univ Sch Med, Dept Biochem & Mol Biol, Indianapolis, IN 46202 USA.
Recommended Citation
GB/T 7714
Faraggi, E,Zhou, YQ,Kloczkowski, A,et al. Accurate single-sequence prediction of solvent accessible surface area using local and global features[J]. PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS,2014,82(11):3170-3176.
APA Faraggi, E,Zhou, YQ,Kloczkowski, A,&Faraggi, E .(2014).Accurate single-sequence prediction of solvent accessible surface area using local and global features.PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS,82(11),3170-3176.
MLA Faraggi, E,et al."Accurate single-sequence prediction of solvent accessible surface area using local and global features".PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 82.11(2014):3170-3176.
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