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 paperpeer-review

    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
    Country/TerritoryUnited States
    CityLas Vegas, NV
    Period31/03/0804/04/08

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