alexa Identification of DNA-binding proteins using support vector machines and evolutionary profiles.
Psychiatry

Psychiatry

Clinical Depression

Author(s): Kumar M, Gromiha MM, Raghava GP

Abstract Share this page

Abstract BACKGROUND: Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation, as these proteins play a crucial role in gene-regulation. In this paper, we developed various SVM modules for predicting DNA-binding domains and proteins. All models were trained and tested on multiple datasets of non-redundant proteins. RESULTS: SVM models have been developed on DNAaset, which consists of 1153 DNA-binding and equal number of non DNA-binding proteins, and achieved the maximum accuracy of 72.42\% and 71.59\% using amino acid and dipeptide compositions, respectively. The performance of SVM model improved from 72.42\% to 74.22\%, when evolutionary information in form of PSSM profiles was used as input instead of amino acid composition. In addition, SVM models have been developed on DNAset, which consists of 146 DNA-binding and 250 non-binding chains/domains, and achieved the maximum accuracy of 79.80\% and 86.62\% using amino acid composition and PSSM profiles. The SVM models developed in this study perform better than existing methods on a blind dataset. CONCLUSION: A highly accurate method has been developed for predicting DNA-binding proteins using SVM and PSSM profiles. This is the first study in which evolutionary information in form of PSSM profiles has been used successfully for predicting DNA-binding proteins. A web-server DNAbinder has been developed for identifying DNA-binding proteins and domains from query amino acid sequences http://www.imtech.res.in/raghava/dnabinder/.
This article was published in BMC Bioinformatics and referenced in Clinical Depression

Relevant Expert PPTs

Relevant Speaker PPTs

Recommended Conferences

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

 
© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
adwords