Allegro: Analyzing expression and sequence in concert to discover regulatory programs Export

@article{citeulike:3929782, abstract = {A major goal of system biology is the characterization of transcription factors and microRNAs (miRNAs) and the transcriptional programs they regulate. We present Allegro, a method for de-novo discovery of cis-regulatory transcriptional programs through joint analysis of genome-wide expression data and promoter or 3' UTR sequences. The algorithm uses a novel log-likelihood-based, non-parametric model to describe the expression pattern shared by a group of co-regulated genes. We show that Allegro is more accurate and sensitive than existing techniques, and can simultaneously analyze multiple expression datasets with more than 100 conditions. We apply Allegro on datasets from several species and report on the transcriptional modules it uncovers. Our analysis reveals a novel motif over-represented in the promoters of genes highly expressed in murine oocytes, and several new motifs related to fly development. Finally, using stem-cell expression profiles, we identify three miRNA families with pivotal roles in human embryogenesis. 10.1093/nar/gkn1064}, author = {Halperin, Yonit and Linhart, Chaim and Ulitsky, Igor and Shamir, Ron}, booktitle = {Nucl. Acids Res.}, citeulike-article-id = {3929782}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/nar/gkn1064}, citeulike-linkout-1 = {http://nar.oxfordjournals.org/content/37/5/1566.abstract}, citeulike-linkout-2 = {http://nar.oxfordjournals.org/content/37/5/1566.full.pdf}, citeulike-linkout-3 = {http://nar.oxfordjournals.org/cgi/content/abstract/37/5/1566}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/19151090}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=19151090}, day = {1}, doi = {10.1093/nar/gkn1064}, journal = {Nucl. Acids Res.}, keywords = {modules, motif\_discovery, tfnets, tfprograms}, month = {April}, number = {5}, pages = {1566--1579}, posted-at = {2009-11-12 23:15:41}, priority = {2}, title = {Allegro: Analyzing expression and sequence in concert to discover regulatory programs}, url = {http://dx.doi.org/10.1093/nar/gkn1064}, volume = {37}, year = {2009} }

TY - JOUR ID - citeulike:3929782 L3 - citeulike-article-id:3929782 N2 - A major goal of system biology is the characterization of transcription factors and microRNAs (miRNAs) and the transcriptional programs they regulate. We present Allegro, a method for de-novo discovery of cis-regulatory transcriptional programs through joint analysis of genome-wide expression data and promoter or 3' UTR sequences. The algorithm uses a novel log-likelihood-based, non-parametric model to describe the expression pattern shared by a group of co-regulated genes. We show that Allegro is more accurate and sensitive than existing techniques, and can simultaneously analyze multiple expression datasets with more than 100 conditions. We apply Allegro on datasets from several species and report on the transcriptional modules it uncovers. Our analysis reveals a novel motif over-represented in the promoters of genes highly expressed in murine oocytes, and several new motifs related to fly development. Finally, using stem-cell expression profiles, we identify three miRNA families with pivotal roles in human embryogenesis. 10.1093/nar/gkn1064 IS - 5 JF - Nucl. Acids Res. EP - 1579 TI - Allegro: Analyzing expression and sequence in concert to discover regulatory programs VL - 37 T2 - Nucl. Acids Res. SP - 1566 KW - modules KW - motif_discovery KW - tfnets KW - tfprograms AU - Halperin, Yonit AU - Linhart, Chaim AU - Ulitsky, Igor AU - Shamir, Ron PY - 2009/04/01/ UR - http://dx.doi.org/10.1093/nar/gkn1064 ER -