GOASVM: Protein subcellular localization prediction based on Gene ontology annotation and SVM

Shibiao Wan, Man Wai Mak, Sun-Yuan Kung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Protein subcellular localization is an essential step to annotate proteins and to design drugs. This paper proposes a functional-domain based method-GOASVM-by making full use of Gene Ontology Annotation (GOA) database to predict the subcellular locations of proteins. GOASVM uses the accession number (AC) of a query protein and the accession numbers (ACs) of homologous proteins returned from PSI-BLAST as the query strings to search against the GOA database. The occurrences of a set of predefined GO terms are used to construct the GO vectors for classification by support vector machines (SVMs). The paper investigated two different approaches to constructing the GO vectors. Experimental results suggest that using the ACs of homologous proteins as the query strings can achieve an accuracy of 94.68%, which is significantly higher than all published results based on the same dataset. As a user-friendly web-server, GOASVM is freely accessible to the public at http://bioinfo.eie. polyu.edu.hk/mGoaSvmServer/GOASVM.html.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages2229-2232
Number of pages4
DOIs
StatePublished - Oct 23 2012
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
Duration: Mar 25 2012Mar 30 2012

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
CountryJapan
CityKyoto
Period3/25/123/30/12

All Science Journal Classification (ASJC) codes

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

Keywords

  • GO terms
  • Gene Ontology
  • Gene Ontology Annotation
  • Protein subcellular localization
  • Support vector machines

Fingerprint Dive into the research topics of 'GOASVM: Protein subcellular localization prediction based on Gene ontology annotation and SVM'. Together they form a unique fingerprint.

  • Cite this

    Wan, S., Mak, M. W., & Kung, S-Y. (2012). GOASVM: Protein subcellular localization prediction based on Gene ontology annotation and SVM. In 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings (pp. 2229-2232). [6288356] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2012.6288356