Reconstruct modular phenotype-specific gene networks by knowledge-driven matrix factorization

Xuerui Yang, Yang Zhou, Rong Jin, Christina Chan

    Research output: Research - peer-reviewArticle

    • 14 Citations

    Abstract

    Motivation: Reconstructing gene networks from microarray data has provided mechanistic information on cellular processes. A popular structure learning method, Bayesian network inference, has been used to determine network topology despite its shortcomings, i.e. the high-computational cost when analyzing a large number of genes and the inefficiency in exploiting prior knowledge, such as the co-regulation information of the genes. To address these limitations, we are introducing an alternative method, knowledge-driven matrix factorization (KMF) framework, to reconstruct phenotype-specific modular gene networks. Results: Considering the reconstruction of gene network as a matrix factorization problem, we first use the gene expression data to estimate a correlation matrix, and then factorize the correlation matrix to recover the gene modules and the interactions between them. Prior knowledge from Gene Ontology is integrated into the matrix factorization. We applied this KMF algorithm to hepatocellular carcinoma (HepG2) cells treated with free fatty acids (FFAs). By comparing the module networks for the different conditions, we identified the specific modules that are involved in conferring the cytotoxic phenotype induced by palmitate. Further analysis of the gene modules of the different conditions suggested individual genes that play important roles in palmitate-induced cytotoxicity. In summary, KMF can efficiently integrate gene expression data with prior knowledge, thereby providing a powerful method of reconstructing phenotype-specific gene networks and valuable insights into the mechanisms that govern the phenotype.

    LanguageEnglish (US)
    Pages2236-2243
    Number of pages8
    JournalBioinformatics
    Volume25
    Issue number17
    DOIs
    StatePublished - 2009

    Profile

    Gene Networks
    Matrix Factorization
    Phenotype
    Gene
    Knowledge
    Gene Regulatory Networks
    Factorization
    Genes
    Module
    Prior Knowledge
    Correlation Matrix
    Gene Expression Data
    Palmitates
    Gene Expression
    Factorise
    Structure Learning
    Cytotoxicity
    Gene Ontology
    Fatty Acids
    Microarray Data

    ASJC Scopus subject areas

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

    Cite this

    Reconstruct modular phenotype-specific gene networks by knowledge-driven matrix factorization. / Yang, Xuerui; Zhou, Yang; Jin, Rong; Chan, Christina.

    In: Bioinformatics, Vol. 25, No. 17, 2009, p. 2236-2243.

    Research output: Research - peer-reviewArticle

    Yang, Xuerui ; Zhou, Yang ; Jin, Rong ; Chan, Christina. / Reconstruct modular phenotype-specific gene networks by knowledge-driven matrix factorization. In: Bioinformatics. 2009 ; Vol. 25, No. 17. pp. 2236-2243
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