Graph kernel-based learning for gene function prediction from gene interaction network

Xin Li, Zhu Zhang, Hsinchun Chen, Jiexun Li

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

5 Citations (Scopus)

Abstract

Prediction of gene functions is a major challenge to biologists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer gene functions. Most previous studies used heuristic approaches based on either local or global information of gene interaction networks to assign unknown gene functions. In this study, we propose a graph kernel-based method that can capture the structure of gene interaction networks to predict gene functions. We conducted an experimental study on a test-bed of P53-related genes. The experimental results demonstrated better performance for our proposed method as compared with baseline methods.

Original languageEnglish (US)
Title of host publicationProceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007
Pages368-373
Number of pages6
DOIs
StatePublished - 2007
Event2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007 - Fremont, CA, United States
Duration: Nov 2 2007Nov 4 2007

Other

Other2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007
CountryUnited States
CityFremont, CA
Period11/2/0711/4/07

Fingerprint

Gene Regulatory Networks
Genes
Learning
p53 Genes

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science(all)
  • Biomedical Engineering

Cite this

Li, X., Zhang, Z., Chen, H., & Li, J. (2007). Graph kernel-based learning for gene function prediction from gene interaction network. In Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007 (pp. 368-373). [4413079] https://doi.org/10.1109/BIBM.2007.25

Graph kernel-based learning for gene function prediction from gene interaction network. / Li, Xin; Zhang, Zhu; Chen, Hsinchun; Li, Jiexun.

Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007. 2007. p. 368-373 4413079.

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

Li, X, Zhang, Z, Chen, H & Li, J 2007, Graph kernel-based learning for gene function prediction from gene interaction network. in Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007., 4413079, pp. 368-373, 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007, Fremont, CA, United States, 11/2/07. https://doi.org/10.1109/BIBM.2007.25
Li X, Zhang Z, Chen H, Li J. Graph kernel-based learning for gene function prediction from gene interaction network. In Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007. 2007. p. 368-373. 4413079 https://doi.org/10.1109/BIBM.2007.25
Li, Xin ; Zhang, Zhu ; Chen, Hsinchun ; Li, Jiexun. / Graph kernel-based learning for gene function prediction from gene interaction network. Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2007. 2007. pp. 368-373
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