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Mania: A Gene Network Reverse Algorithm For Compounds Mode-Of-Action And Genes Interactions Inference

Author

Listed:
  • DARONG LAI

    (Department of Computer Science and Engineering, Shanghai Jiao Tong University, China;
    CAS-MPG Partner Institute for Computational Biology, Yue Yuan Road 320, Shanghai, China)

  • HONGTAO LU

    (Department of Computer Science and Engineering, Shanghai Jiao Tong University, China)

  • MARIO LAURIA

    (TIGEM, 111 Via Pietro Castellino, Naples, Italy)

  • DIGEO DI BERNARDO

    (TIGEM, 111 Via Pietro Castellino, Naples, Italy)

  • CHRISTINE NARDINI

    (CAS-MPG Partner Institute for Computational Biology, Yue Yuan Road 320, Shanghai, China)

Abstract

Understanding the complexity of the cellular machinery represents a grand challenge in molecular biology. To contribute to the deconvolution of this complexity, a novel inference algorithm based on linear ordinary differential equations is proposed, based solely on high-throughput gene expression data. The algorithm can infer (i) gene–gene interactions from steady state expression profiles and (ii) mode-of-action of the components that can trigger changes in the system. Results demonstrate that the proposed algorithm can identifybothinformation with high performances, thus overcoming the limitation of current algorithms that can infer reliably only one.

Suggested Citation

  • Darong Lai & Hongtao Lu & Mario Lauria & Digeo Di Bernardo & Christine Nardini, 2010. "Mania: A Gene Network Reverse Algorithm For Compounds Mode-Of-Action And Genes Interactions Inference," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 83-94.
    • Handle: RePEc:wsi:acsxxx:v:13:y:2010:i:01:n:s0219525910002451
    DOI: 10.1142/S0219525910002451
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