ARACNE

Introduction
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.
On some specific synthetic datasets ARACNE achieved low error rates and outperformed other methods, such as Relevance Networks and Bayesian Networks. Application to the deconvolution of genetic networks in human B cells demonstrated ARACNE’s ability to infer validated transcriptional targets of the c-MYC proto-oncogene.
ARACNE is now widely used together with a set of other network reconstruction algorithms. This approach should enhance our ability to use microarray data to elucidate functional mechanisms that underlie cellular processes and to identify molecular targets of pharmacological compounds in mammalian cellular networks.
Relevant Publications
1) Reverse engineering cellular networks. Nature Protocols 1, 662 - 671 (2006). (Download PDF) (Supplemental Documents)
2) Reverse engineering of regulatory networks in human B cells. Nature Genetics. 2005 Apr;37(4):382-90. (Download PDF)
3) ARACNE: An Algorithm for the Reconstruction of Gene Regulatory Networks in a Mammalian Cellular Context.
In press in BMC Bioinformatic. (Download PDF)
4) On The Reconstruction of Interaction Networks with Applications to Transcriptional Regulation.
http://arxiv.org/abs/q-bio.MN/0410036. Accepted in NIPS 2005
5) Conditional Network Analysis Identifies Candidate Regulator Genes in Human B Cells.
http://arxiv.org/abs/q-bio/?0411003. Submitted to RECOMB 2005

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