MANIA: A GENE NETWORK REVERSE ALGORITHM FOR COMPOUNDS MODE-OF-ACTION AND GENES INTERACTIONS INFERENCE

Darong Lai (), Hongtao Lu, Mario Lauria, Digeo Di Bernardo and Christine Nardini ()
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Darong Lai: Department of Computer Science and Engineering, Shanghai Jiao Tong University, 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

Advances in Complex Systems (ACS), 2010, vol. 13, issue 01, 83-94

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.

Keywords: Gene network; gene expression; reverse engineering; ordinary differential equations (ODE); compound mode-of-action (search for similar items in EconPapers)
Date: 2010
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DOI: 10.1142/S0219525910002451

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