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Incorporation of biological knowledge into distance for clustering genes.

ABSTRACT: UNLABELLED:In this paper we propose a data based algorithm to marry existing biological knowledge (e.g., functional annotations of genes) with experimental data (gene expression profiles) in creating an overall dissimilarity that can be used with any clustering algorithm that uses a general dissimilarity matrix. We explore this idea with two publicly available gene expression data sets and functional annotations where the results are compared with the clustering results that uses only the experimental data. Although more elaborate evaluations might be called for, the present paper makes a strong case for utilizing existing biological information in the clustering process. AVAILABILITY:Supplement is available at www.somnathdatta.org/Supp/Bioinformation/appendix.pdf.

SUBMITTER: Boratyn GM

PROVIDER: S-EPMC1896054 | biostudies-literature | 2007 Apr

REPOSITORIES: biostudies-literature

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Incorporation of biological knowledge into distance for clustering genes.

Boratyn Grzegorz M GM Datta Susmita S Datta Somnath S

Bioinformation 20070410 10

<h4>Unlabelled</h4>In this paper we propose a data based algorithm to marry existing biological knowledge (e.g., functional annotations of genes) with experimental data (gene expression profiles) in creating an overall dissimilarity that can be used with any clustering algorithm that uses a general dissimilarity matrix. We explore this idea with two publicly available gene expression data sets and functional annotations where the results are compared with the clustering results that uses only th ...[more]

PMID: 17597929

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Incorporation of biological knowledge into distance for clustering genes.

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Incorporation of biological knowledge into distance for clustering genes.

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