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

Shibiao Wan; Man Wai Mak; Sun Yuan Kung

doi:10.1109/ICASSP.2012.6288356

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

Shibiao Wan, Man Wai Mak, Sun Yuan Kung

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

13 Citations (Scopus)

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 language	English
Title of host publication	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages	2229-2232
Number of pages	4
DOIs	https://doi.org/10.1109/ICASSP.2012.6288356
Publication status	Published - 23 Oct 2012
Event	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan Duration: 25 Mar 2012 → 30 Mar 2012

Conference

Conference	2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Country/Territory	Japan
City	Kyoto
Period	25/03/12 → 30/03/12

Keywords

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

ASJC Scopus subject areas

Software
Signal Processing
Electrical and Electronic Engineering

More information

10.1109/ICASSP.2012.6288356

Cite this

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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.",

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Wan, S, Mak, MW & Kung, SY 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., 6288356, pp. 2229-2232, 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012, Kyoto, Japan, 25/03/12. https://doi.org/10.1109/ICASSP.2012.6288356

GOASVM: Protein subcellular localization prediction based on Gene ontology annotation and SVM. / Wan, Shibiao; Mak, Man Wai; Kung, Sun Yuan.
2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings. 2012. p. 2229-2232 6288356.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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

Abstract

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Keywords

ASJC Scopus subject areas

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