Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory

Yinyin Yuan, Chang Tsun Li

Research output: Book chapter/Published conference paperConference paper

1 Citation (Scopus)

Abstract

Based on the correlation between expression and ontology-driven gene similarity, we incorporate functional annotations into gene expression clustering validation. A probabilistic framework is proposed to accommodate incomplete annotations, after establishing a new term-term distance measure based on graph theory. Comprehensive evaluations are performed on six clustering algorithms. This study is the first to explore a robust quantitative functional relationship between clusters of genes. Such indices assess clustering quality in terms of consistency of annotation information and serve as new tools for combining biological knowledge with experimental data.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages625-628
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 31 Mar 200804 Apr 2008

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period31/03/0804/04/08

Fingerprint Dive into the research topics of 'Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory'. Together they form a unique fingerprint.

  • Cite this

    Yuan, Y., & Li, C. T. (2008). Probabilistic framework for gene expression clustering validation based on gene ontology and graph theory. In 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP (pp. 625-628). [4517687] https://doi.org/10.1109/ICASSP.2008.4517687