Literature DB >> 21802968

OligoPred: a web-server for predicting homo-oligomeric proteins by incorporating discrete wavelet transform into Chou's pseudo amino acid composition.

Jian-Ding Qiu1, Sheng-Bao Suo, Xing-Yu Sun, Shao-Ping Shi, Ru-Ping Liang.   

Abstract

In vivo, some proteins exist as monomers (single polypeptide chains) and others as oligomers. Not like monomers, oligomers are composed of two or more chains (subunits) that are associated with each other through non-covalent interactions and, occasionally, through disulfide bonds. These proteins are the structural components of various biological functions, including cooperative effects, allosteric mechanisms and ion-channel gating. However, with the dramatic increase in the number of protein sequences submitted to the public data bank, it is important for both basic research and drug discovery research to acquire the possible knowledge about homo-oligomeric attributes of their interested proteins in a timely manner. In this paper, a high-throughput method, combined support vector machines with discrete wavelet transform, has been developed to predict the protein homo-oligomers. The total accuracy obtained by the re-substitution test, jackknife test and independent dataset test are 99.94%, 96.17% and 96.18%, respectively, showing that the proposed method of extracting feature from the protein sequences is effective and feasible for predicting homo-oligomers. The online service is available at http://bioinfo.ncu.edu.cn/Services.aspx.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 21802968     DOI: 10.1016/j.jmgm.2011.06.014

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  7 in total

Review 1.  Some illuminating remarks on molecular genetics and genomics as well as drug development.

Authors:  Kuo-Chen Chou
Journal:  Mol Genet Genomics       Date:  2020-01-01       Impact factor: 3.291

2.  Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection.

Authors:  Samad Jahandideh; Vinodh Srinivasasainagendra; Degui Zhi
Journal:  J Theor Biol       Date:  2012-08-03       Impact factor: 2.691

3.  iNR-PhysChem: a sequence-based predictor for identifying nuclear receptors and their subfamilies via physical-chemical property matrix.

Authors:  Xuan Xiao; Pu Wang; Kuo-Chen Chou
Journal:  PLoS One       Date:  2012-02-21       Impact factor: 3.240

4.  A multi-label predictor for identifying the subcellular locations of singleplex and multiplex eukaryotic proteins.

Authors:  Xiao Wang; Guo-Zheng Li
Journal:  PLoS One       Date:  2012-05-22       Impact factor: 3.240

5.  osFP: a web server for predicting the oligomeric states of fluorescent proteins.

Authors:  Saw Simeon; Watshara Shoombuatong; Nuttapat Anuwongcharoen; Likit Preeyanon; Virapong Prachayasittikul; Jarl E S Wikberg; Chanin Nantasenamat
Journal:  J Cheminform       Date:  2016-12-20       Impact factor: 5.514

6.  PseAAC-General: fast building various modes of general form of Chou's pseudo-amino acid composition for large-scale protein datasets.

Authors:  Pufeng Du; Shuwang Gu; Yasen Jiao
Journal:  Int J Mol Sci       Date:  2014-02-26       Impact factor: 5.923

7.  iSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition.

Authors:  Wei Chen; Peng-Mian Feng; Hao Lin; Kuo-Chen Chou
Journal:  Biomed Res Int       Date:  2014-05-21       Impact factor: 3.411

  7 in total

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