Protein subcellular localization prediction using multiple kernel learning based support vector machine-Reference-Cited by-同舟云学术

Protein subcellular localization prediction using multiple kernel learning based support vector machine

Published:2017 Issue:4 Volume:13 Page:785-795
ISSN:1742-206X
Container-title:Molecular BioSystems
language:en
Short-container-title:Mol. BioSyst.

Author:

Hasan Md. Al Mehedi¹²³⁴^ORCID,Ahmad Shamim¹²³⁴,Molla Md. Khademul Islam¹²³⁴

Affiliation:

1. Department of Computer Science & Engineering

2. University of Rajshahi

3. Rajshahi

4. Bangladesh

Abstract

An efficient multi-label protein subcellular localization prediction system was developed by introducing multiple kernel learning (MKL) based support vector machine (SVM).

Publisher

Royal Society of Chemistry (RSC)

Subject

Molecular Biology,Biotechnology

Link

http://pubs.rsc.org/en/content/articlepdf/2017/MB/C6MB00860G

Reference73 articles.

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4. S. Wan , M. W.Mak and S. Y.Kung, GOASVM: Protein subcellular localization prediction based on gene ontology annotation and SVM, Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on, IEEE, 2012, pp. 2229–2232

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