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Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures.

Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures. Research Abstract Details 

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  • Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures. Abstract Text:

    BACKGROUND: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting information on this genomic scale, and a first step towards the rapid and comprehensive interpretation of this data is gene clustering with respect to the expression patterns. Classifying genes into clusters can lead to interesting biological insights. In this study, we describe an iterative clustering approach to uncover biologically coherent structures from DNA microarray data based on a novel clustering algorithm EP_GOS_Clust. RESULTS: We apply our proposed iterative algorithm to three sets of experimental DNA microarray data from experiments with the yeast Saccharomyces cerevisiae and show that the proposed iterative approach improves biological coherence. Comparison with other clustering techniques suggests that our iterative algorithm provides superior performance with regard to biological coherence. An important consequence of our approach is that an increasing proportion of genes find membership in clusters of high biological coherence and that the average cluster specificity improves. CONCLUSION: The results from these clustering experiments provide a robust basis for extracting motifs and trans-acting factors that determine particular patterns of expression. In addition, the biological coherence of the clusters is iteratively assessed independently of the clustering. Thus, this method will not be severely impacted by functional annotations that are missing, inaccurate, or sparse.

    Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures. Publishing Authors By Initials

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    Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures. Journal Published:

    PUBLICATION TYPE: Research Support, U.S. Gov't,

    Journal: BMC bioinformatics

    VOLUME: 9

    Page Numbers: 268

    Journal Abbreviation: BMC Bioinformatics

    ISSN: 1471-2105

    DAY: 6

    MONTH: 06

    YEAR: 2008

    Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures. Information

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    LANGUAGE: eng

    NlmUniqueID: 100965194

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    Grant and Affiliation Information for Microarray data mining: a novel optimization-based approach to uncover biologically coherent structures.

    AFFILIATION: Department of Chemical Engineering, Princeton University, NJ, USA. mtan@princeton.edu

    Country: England

    England Research Publication

    AGENCY: United States NIGMS

    GRANT: P50 GM71508

    ACRONYM: GM

    MEDLINETA: BMC Bioinformatics

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