Gene Network Inference

Provides Objective-C (Cocoa for Mac, GNUstep for Linux/Windows) optimization framework to learn linear gene regulatory networks from various types of gene expression data. The optimization incorporates network sparsity constraint through L1 regularization as well as incorporation of existing network information. The framework can handle wild type, perturbation, gene knockout and heterozygous knockdown gene expression data.

Center/Contributor: Center for Mathematical & Computational Biology

Contact: Qing Nie

2011 Gene Network Inference. Copyright © 2013. The Center for Complex Biological Systems, UC Irvine
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