Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis.

Yoshihiro Yamanishi, J. P. Vert, A. Nakaya, M. Kanehisa

    Research output: Contribution to journalArticle

    82 Citations (Scopus)

    Abstract

    MOTIVATION: A major issue in computational biology is the reconstruction of pathways from several genomic datasets, such as expression data, protein interaction data and phylogenetic profiles. As a first step toward this goal, it is important to investigate the amount of correlation which exists between these data. RESULTS: These methods are successfully tested on their ability to recognize operons in the Escherichia coli genome, from the comparison of three datasets corresponding to functional relationships between genes in metabolic pathways, geometrical relationships along the chromosome, and co-expression relationships as observed by gene expression data.

    Original languageEnglish
    JournalBioinformatics (Oxford, England)
    Volume19 Suppl 1
    Publication statusPublished - Jan 1 2003

    All Science Journal Classification (ASJC) codes

    • Statistics and Probability
    • Biochemistry
    • Molecular Biology
    • Computer Science Applications
    • Computational Theory and Mathematics
    • Computational Mathematics

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