ARACNE

ベイジアンネットワークを改良したネットワーク解析アルゴリズム。遺伝子間の相互作用の強さを評価して、間接的な相互作用とみなせる関係を排除し、直接的な相互作用を高い精度で推定することを目指した。

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 synthetic datasets ARACNE achieves extremely low error rates and significantly outperforms established methods, such as Relevance Networks and Bayesian Networks. Application to the deconvolution of genetic networks in human B cells demonstrates ARACNE’s ability to infer validated transcriptional targets of the c-MYC proto-oncogene.

Ex）ヒトB細胞の遺伝子間相互作用推定

Reverse engineering of regulatory networks in human B cells. Nature Genetics. 2005 Apr;37(4):382-90. (Download PDF)