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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
发表期刊PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS
语种英语
关键词Protein Secondary Structure Backbone Torsion Angles Real-value Prediction Regression
摘要We 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
卷号82期号:11页码:3170-3176
学科领域Physics
DOI10.1002/prot.24682
收录类别SCI
项目资助者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] ; 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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被引频次:10[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.itp.ac.cn/handle/311006/15593
专题理论物理所科研产出_SCI论文
通讯作者Faraggi, E (reprint author), Indiana Univ Sch Med, Dept Biochem & Mol Biol, Indianapolis, IN 46202 USA.
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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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