Classifying g-protein coupled receptors with hydropathy blocks and support vector machines

Xing Ming Zhao; D. Shuang Huang; Shiwu Zhang; Yiu Ming CHEUNG

doi:10.1007/11816102_63

Classifying g-protein coupled receptors with hydropathy blocks and support vector machines

Xing Ming Zhao^*, D. Shuang Huang, Shiwu Zhang, Yiu Ming CHEUNG

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

1 Citation (Scopus)

Abstract

This paper developes a new method for recognizing G-Protein Coupled Receptors (GPCRs) based on features generated from the hydropathy properties of the amino acid sequences. Using the hydropathy characteristics, namely hydropathy blocks, the protein sequences are converted into fixed-dimensional feature vectors. Subsequently, the Support Vector Machine (SVM) classifier is utilized to identify the GPCR proteins belonging to the same families or subfamilies. The experimental results on GPCR datasets show that the proteins belonging to the same family or subfamily can be identified using features generated based on the hydropathy blocks.

Original language	English
Title of host publication	Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings
Publisher	Springer Verlag
Pages	593-602
Number of pages	10
ISBN (Print)	3540372776, 9783540372776
DOIs	https://doi.org/10.1007/11816102_63
Publication status	Published - 2006
Event	International Conference on Intelligent Computing, ICIC 2006 - Kunming, China Duration: 16 Aug 2006 → 19 Aug 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4115 LNBI -III
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Intelligent Computing, ICIC 2006
Country/Territory	China
City	Kunming
Period	16/08/06 → 19/08/06

Scopus Subject Areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/11816102_63

Cite this

Zhao, X. M., Huang, D. S., Zhang, S., & CHEUNG, Y. M. (2006). Classifying g-protein coupled receptors with hydropathy blocks and support vector machines. In Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings (pp. 593-602). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4115 LNBI -III). Springer Verlag. https://doi.org/10.1007/11816102_63

Zhao, Xing Ming ; Huang, D. Shuang ; Zhang, Shiwu et al. / Classifying g-protein coupled receptors with hydropathy blocks and support vector machines. Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings. Springer Verlag, 2006. pp. 593-602 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{3252e3f17b0c458a884eeecc59b7bf01,

title = "Classifying g-protein coupled receptors with hydropathy blocks and support vector machines",

abstract = "This paper developes a new method for recognizing G-Protein Coupled Receptors (GPCRs) based on features generated from the hydropathy properties of the amino acid sequences. Using the hydropathy characteristics, namely hydropathy blocks, the protein sequences are converted into fixed-dimensional feature vectors. Subsequently, the Support Vector Machine (SVM) classifier is utilized to identify the GPCR proteins belonging to the same families or subfamilies. The experimental results on GPCR datasets show that the proteins belonging to the same family or subfamily can be identified using features generated based on the hydropathy blocks.",

author = "Zhao, {Xing Ming} and Huang, {D. Shuang} and Shiwu Zhang and CHEUNG, {Yiu Ming}",

year = "2006",

doi = "10.1007/11816102_63",

language = "English",

isbn = "3540372776",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "593--602",

booktitle = "Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings",

address = "Germany",

}

Zhao, XM, Huang, DS, Zhang, S & CHEUNG, YM 2006, Classifying g-protein coupled receptors with hydropathy blocks and support vector machines. in Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4115 LNBI -III, Springer Verlag, pp. 593-602, International Conference on Intelligent Computing, ICIC 2006, Kunming, China, 16/08/06. https://doi.org/10.1007/11816102_63

Classifying g-protein coupled receptors with hydropathy blocks and support vector machines. / Zhao, Xing Ming; Huang, D. Shuang; Zhang, Shiwu et al.
Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings. Springer Verlag, 2006. p. 593-602 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4115 LNBI -III).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Classifying g-protein coupled receptors with hydropathy blocks and support vector machines

AU - Zhao, Xing Ming

AU - Huang, D. Shuang

AU - Zhang, Shiwu

AU - CHEUNG, Yiu Ming

PY - 2006

Y1 - 2006

N2 - This paper developes a new method for recognizing G-Protein Coupled Receptors (GPCRs) based on features generated from the hydropathy properties of the amino acid sequences. Using the hydropathy characteristics, namely hydropathy blocks, the protein sequences are converted into fixed-dimensional feature vectors. Subsequently, the Support Vector Machine (SVM) classifier is utilized to identify the GPCR proteins belonging to the same families or subfamilies. The experimental results on GPCR datasets show that the proteins belonging to the same family or subfamily can be identified using features generated based on the hydropathy blocks.

AB - This paper developes a new method for recognizing G-Protein Coupled Receptors (GPCRs) based on features generated from the hydropathy properties of the amino acid sequences. Using the hydropathy characteristics, namely hydropathy blocks, the protein sequences are converted into fixed-dimensional feature vectors. Subsequently, the Support Vector Machine (SVM) classifier is utilized to identify the GPCR proteins belonging to the same families or subfamilies. The experimental results on GPCR datasets show that the proteins belonging to the same family or subfamily can be identified using features generated based on the hydropathy blocks.

UR - http://www.scopus.com/inward/record.url?scp=33749579231&partnerID=8YFLogxK

U2 - 10.1007/11816102_63

DO - 10.1007/11816102_63

M3 - Conference proceeding

AN - SCOPUS:33749579231

SN - 3540372776

SN - 9783540372776

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 593

EP - 602

BT - Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings

PB - Springer Verlag

T2 - International Conference on Intelligent Computing, ICIC 2006

Y2 - 16 August 2006 through 19 August 2006

ER -

Zhao XM, Huang DS, Zhang S, CHEUNG YM. Classifying g-protein coupled receptors with hydropathy blocks and support vector machines. In Computational Intelligence and Bioinformatics International Conference on Intelligent Computing, ICIC 2006, Proceedings. Springer Verlag. 2006. p. 593-602. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11816102_63

Classifying g-protein coupled receptors with hydropathy blocks and support vector machines

Abstract

Publication series

Conference

Scopus Subject Areas

Access to Document

Other files and links

Fingerprint

Cite this