GRNInfer aims to derive the most consistent network structure with respect to Multiple Microarray Datasets, by exploiting available information from a variety of experiments. Specifically, inferring gene network is formulated as an optimization problem with minimization of L1 norm for the objective function, which involves both forced matching and sparse terms. An efficient algorithm is developed to solve such a large-scale linear programming in an iterative manner. With such a procedure, a consistent and sparse structure that is also considered to be biologically plausible, can be expected to be derived.
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Yong Wang, Trupti Joshi, Xiang-Sun Zhang, Dong Xu, and Luonan Chen.
Inferring gene regulatory networks from multiple microarray datasets.
Bioinformatics, Vol. 22, No. 19, pp. 2413-2420, 2006.