Network inference algorithm to address a wide range of network deconvolution problems available through Cyni
**ARACNE** (Algorithm for the Reconstruction of Accurate Cellular Networks), a novel algorithm, using microarray expression profiles, specifically designed to scale up to the complexity of regulatory networks in mammalian cells, yet general enough to address a wider range of network deconvolution problems. This method uses an information theoretic approach to eliminate the vast majority of indirect interactions typically inferred by pairwise analysis. This app makes the ARACNE network inference algorithm available to all users through the [ Cyni Toolbox] panel under the *Infer Network* tab. **Relevant Publications and Online References** 1. Reverse engineering cellular networks. Nature Protocols 1, 662 - 671 (2006). [ Nature] 2. Reverse engineering of regulatory networks in human B cells. Nature Genetics. 2005 Apr;37(4):382-90. [ Nature] 3. ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context. In press in BMC Bioinformatics. [ BMC Bioinformtics] 4. On The Reconstruction of Interaction Networks with Applications to Transcriptional Regulation. [ arXiv]. Accepted in NIPS 2005 5. Conditional Network Analysis Identifies Candidate Regulator Genes in Human B Cells. [ arXiv]. Submitted to RECOMB 2005 6. Wikipedia entry: [ wikipedia] 7. Andrea Califano lab ARACNE download website: [ lab website] 8. ARACNE citations on Pubmed: [ ARACNE citations]


Works with Cytoscape 3.1


Version 1.0.0.beta1

Released 27 Aug 2014

Works with Cytoscape 3.1

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