Literature DB >> 19356130

Prediction of cell wall lytic enzymes using Chou's amphiphilic pseudo amino acid composition.

Hui Ding1, Liaofu Luo, Hao Lin.   

Abstract

Discriminating cell wall lytic enzymes from non lytic enzymes is a very important task for curing bacterial infections. In this paper, based on Chou's amphiphilic pseudo amino acid composition, we develop fisher-discriminant based classifier to predict cell wall lytic enzymes. Experiments show that 66.7% sensitivity with 88.6% specificity is obtained. The method is further able to predict endolysin and autolysin with an overall accuracy of 92.9%. Results demonstrated that our method can provide highly useful information for further bacterial control research.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19356130     DOI: 10.2174/092986609787848045

Source DB:  PubMed          Journal:  Protein Pept Lett        ISSN: 0929-8665            Impact factor:   1.890


  34 in total

1.  iRSpot-GAEnsC: identifing recombination spots via ensemble classifier and extending the concept of Chou's PseAAC to formulate DNA samples.

Authors:  Muhammad Kabir; Maqsood Hayat
Journal:  Mol Genet Genomics       Date:  2015-08-30       Impact factor: 3.291

2.  Quat-2L: a web-server for predicting protein quaternary structural attributes.

Authors:  Xuan Xiao; Pu Wang; Kuo-Chen Chou
Journal:  Mol Divers       Date:  2010-02-11       Impact factor: 2.943

3.  Identification of ATP binding residues of a protein from its primary sequence.

Authors:  Jagat S Chauhan; Nitish K Mishra; Gajendra P S Raghava
Journal:  BMC Bioinformatics       Date:  2009-12-19       Impact factor: 3.169

4.  EuLoc: a web-server for accurately predict protein subcellular localization in eukaryotes by incorporating various features of sequence segments into the general form of Chou's PseAAC.

Authors:  Tzu-Hao Chang; Li-Ching Wu; Tzong-Yi Lee; Shu-Pin Chen; Hsien-Da Huang; Jorng-Tzong Horng
Journal:  J Comput Aided Mol Des       Date:  2013-01-03       Impact factor: 3.686

5.  Analysis and prediction of cancerlectins using evolutionary and domain information.

Authors:  Ravi Kumar; Bharat Panwar; Jagat S Chauhan; Gajendra Ps Raghava
Journal:  BMC Res Notes       Date:  2011-07-20

6.  Predicting drug-target interaction networks based on functional groups and biological features.

Authors:  Zhisong He; Jian Zhang; Xiao-He Shi; Le-Le Hu; Xiangyin Kong; Yu-Dong Cai; Kuo-Chen Chou
Journal:  PLoS One       Date:  2010-03-11       Impact factor: 3.240

7.  A new method for predicting the subcellular localization of eukaryotic proteins with both single and multiple sites: Euk-mPLoc 2.0.

Authors:  Kuo-Chen Chou; Hong-Bin Shen
Journal:  PLoS One       Date:  2010-04-01       Impact factor: 3.240

8.  Analysis and prediction of the metabolic stability of proteins based on their sequential features, subcellular locations and interaction networks.

Authors:  Tao Huang; Xiao-He Shi; Ping Wang; Zhisong He; Kai-Yan Feng; Lele Hu; Xiangyin Kong; Yi-Xue Li; Yu-Dong Cai; Kuo-Chen Chou
Journal:  PLoS One       Date:  2010-06-04       Impact factor: 3.240

9.  Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization.

Authors:  Kuo-Chen Chou; Hong-Bin Shen
Journal:  PLoS One       Date:  2010-06-28       Impact factor: 3.240

10.  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

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.