Reverse engineering cellular networks.

摘要: We describe a computational protocol for the ARACNE algorithm, an information-theoretic method identifying transcriptional interactions between gene products using microarray expression profile data. Similar to other algorithms, predicts potential functional associations among genes, or novel functions uncharacterized by statistical dependencies products. However, based on biochemical validation, literature searches and DNA binding site enrichment analysis, has also proven effective in bona fide targets, even complex mammalian networks. Thus we envision that predictions made ARACNE, especially when supplemented with prior knowledge additional data sources, can provide appropriate hypotheses further investigation of cellular While examples this use only data, algorithm's theoretical basis readily extends variety high-throughput measurements, such as pathway-specific genome-wide proteomics, microRNA metabolomics As these become available, expect might prove increasingly useful elucidating underlying interaction models. For set containing approximately 10,000 probes, reconstructing network around single probe completes several minutes desktop computer Pentium 4 processor. Reconstructing generally requires cluster, if recommended bootstrapping procedure is used.