Predicting protein-protein interaction sites using radial basis function neural networks

Bing Wang; Hau San Wong; Peng Chen; Hong-Qiang Wang; De-Shuang Huang

doi:10.1109/IJCNN.2006.247053

Predicting protein-protein interaction sites using radial basis function neural networks

Bing Wang
, Hau San Wong
, Peng Chen
, Hong-Qiang Wang
, De-Shuang Huang^*

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

11 Citations (Scopus)

Abstract

Identifying protein-protein interaction sites is crucial for understanding of the principles of biological systems and processes, as well as mutant design. This paper describes a novel method that can predict protein interaction sites in heterocomplexes using information of evolutionary conservation and spatial sequence profile. A predictor was generated to distinguish the interface residues from protein surface region by radial basis neural networks, which is trained by expectation maximization algorithm. Based on a non-redundant data set of heterodimers consisting of 75 protein chains, the efficiency and the effectiveness of our proposed approach can be validated by a better performance such as the accuracy of 0.60, the sensitivity of 58.3% and the specificity of 59.9%. © 2006 IEEE.

Original language	English
Title of host publication	The 2006 IEEE International Joint Conference on Neural Network Proceedings
Publisher	IEEE
Pages	2325-2330
ISBN (Print)	0780394909, 9780780394902
DOIs	https://doi.org/10.1109/IJCNN.2006.247053
Publication status	Published - 2006
Event	2006 International Joint Conference on Neural Networks (IJCNN '06) - Vancouver, BC, Canada Duration: 16 Jul 2006 → 21 Jul 2006

Publication series

Name
ISSN (Print)	2161-4393
ISSN (Electronic)	2161-4407

Conference

Conference	2006 International Joint Conference on Neural Networks (IJCNN '06)
Place	Canada
City	Vancouver, BC
Period	16/07/06 → 21/07/06

Access Output

10.1109/IJCNN.2006.247053

Other Access Options

Check CityUHK Library

Permanent Link

Right click to copy link

Cite this

@inproceedings{a6575555779b41478db86c8c27c0cca1,

title = "Predicting protein-protein interaction sites using radial basis function neural networks",

abstract = "Identifying protein-protein interaction sites is crucial for understanding of the principles of biological systems and processes, as well as mutant design. This paper describes a novel method that can predict protein interaction sites in heterocomplexes using information of evolutionary conservation and spatial sequence profile. A predictor was generated to distinguish the interface residues from protein surface region by radial basis neural networks, which is trained by expectation maximization algorithm. Based on a non-redundant data set of heterodimers consisting of 75 protein chains, the efficiency and the effectiveness of our proposed approach can be validated by a better performance such as the accuracy of 0.60, the sensitivity of 58.3\% and the specificity of 59.9\%. {\textcopyright} 2006 IEEE.",

author = "Bing Wang and Wong, \{Hau San\} and Peng Chen and Hong-Qiang Wang and De-Shuang Huang",

year = "2006",

doi = "10.1109/IJCNN.2006.247053",

language = "English",

isbn = "0780394909",

publisher = "IEEE",

pages = "2325--2330",

booktitle = "The 2006 IEEE International Joint Conference on Neural Network Proceedings",

address = "United States",

note = "2006 International Joint Conference on Neural Networks (IJCNN '06) ; Conference date: 16-07-2006 Through 21-07-2006",

}

Wang, B, Wong, HS, Chen, P, Wang, H-Q & Huang, D-S 2006, Predicting protein-protein interaction sites using radial basis function neural networks. in The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE, pp. 2325-2330, 2006 International Joint Conference on Neural Networks (IJCNN '06), Vancouver, BC, Canada, 16/07/06. https://doi.org/10.1109/IJCNN.2006.247053

Predicting protein-protein interaction sites using radial basis function neural networks. / Wang, Bing; Wong, Hau San; Chen, Peng et al.
The 2006 IEEE International Joint Conference on Neural Network Proceedings. IEEE, 2006. p. 2325-2330.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Predicting protein-protein interaction sites using radial basis function neural networks

AU - Wang, Bing

AU - Wong, Hau San

AU - Chen, Peng

AU - Wang, Hong-Qiang

AU - Huang, De-Shuang

PY - 2006

Y1 - 2006

N2 - Identifying protein-protein interaction sites is crucial for understanding of the principles of biological systems and processes, as well as mutant design. This paper describes a novel method that can predict protein interaction sites in heterocomplexes using information of evolutionary conservation and spatial sequence profile. A predictor was generated to distinguish the interface residues from protein surface region by radial basis neural networks, which is trained by expectation maximization algorithm. Based on a non-redundant data set of heterodimers consisting of 75 protein chains, the efficiency and the effectiveness of our proposed approach can be validated by a better performance such as the accuracy of 0.60, the sensitivity of 58.3% and the specificity of 59.9%. © 2006 IEEE.

AB - Identifying protein-protein interaction sites is crucial for understanding of the principles of biological systems and processes, as well as mutant design. This paper describes a novel method that can predict protein interaction sites in heterocomplexes using information of evolutionary conservation and spatial sequence profile. A predictor was generated to distinguish the interface residues from protein surface region by radial basis neural networks, which is trained by expectation maximization algorithm. Based on a non-redundant data set of heterodimers consisting of 75 protein chains, the efficiency and the effectiveness of our proposed approach can be validated by a better performance such as the accuracy of 0.60, the sensitivity of 58.3% and the specificity of 59.9%. © 2006 IEEE.

UR - https://www.scopus.com/pages/publications/40649125828

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-40649125828&origin=recordpage

U2 - 10.1109/IJCNN.2006.247053

DO - 10.1109/IJCNN.2006.247053

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 0780394909

SN - 9780780394902

SP - 2325

EP - 2330

BT - The 2006 IEEE International Joint Conference on Neural Network Proceedings

PB - IEEE

T2 - 2006 International Joint Conference on Neural Networks (IJCNN '06)

Y2 - 16 July 2006 through 21 July 2006

ER -

Predicting protein-protein interaction sites using radial basis function neural networks

Abstract

Publication series

Conference

Access Output

Other Access Options

Permanent Link

Other Files and Links

Fingerprint

Cite this