On the sparse reconstruction of gene networks.
We discuss a heuristic method for the sparse reconstruction of gene networks. The method is based on iterative greedy algorithms, and uses gene expression data from microarray experiments. Also, we show numerically that the greedy algorithms are able to give good approximative solutions to the sparse reconstruction problem even in the presence of significant levels of noise.
Andrecut
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Institute for Biocomplexity and Informatics, University of Calgary, Calgary, Alberta, Canada. mandrecu@ucalgary.ca
Kauffman
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D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks