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10.1093/toxsci/kfv261 http://scihub22266oqcxt.onion/10.1093/toxsci/kfv261 C5009613!5009613!26643261     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26643261&cmd=llinks): Failed to open stream: HTTP request failed! 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Discovery of Transcriptional Targets Regulated by Nuclear Receptors Using a Probabilistic Graphical Model |pdf=|usr=}}{{26643261}} gab.com Text Discovery of Transcriptional Targets Regulated by Nuclear Receptors Using a Probabilistic Graphical Model JO: Toxicol Sci http://www.kidney.de/pget.php?&tw=1&pmid=26643261 #FOAvip Nuclear receptors (NRs) are ligand-activated transcriptional regulators that play vital roles in key biological processes such as growth, differentiation, metabolism, reproduction, and morphogenesis. Disruption of NRs can result in adverse health effects such as NR-mediated endocrine disruption. A comprehensive understanding of core transcriptional targets regulated by NRs helps to elucidate their key biological processes in both toxicological and therapeutic aspects. In this study, we applied a probabilistic graphical model to identify the transcriptional targets of NRs and the biological processes they govern. The Tox21 program profiled a collection of approximate 10?000 environmental chemicals and drugs against a panel of human NRs in a quantitative high-throughput screening format for their NR disruption potential. The Japanese Toxicogenomics Project, one of the most comprehensive efforts in the field of toxicogenomics, generated large-scale gene expression profiles on the effect of 131 compounds (in its first phase of study) at various doses, and different durations, and their combinations. We applied author-topic model to these 2 toxicological datasets, which consists of 11 NRs run in either agonist and/or antagonist mode (18 assays total) and 203 in vitro human gene expression profiles connected by 52 shared drugs. As a result, a set of clusters (topics), which consists of a set of NRs and their associated target genes were determined. Various transcriptional targets of the NRs were identified by assays run in either agonist or antagonist mode. Our results were validated by functional analysis and compared with TRANSFAC data. In summary, our approach resulted in effective identification of associated/affected NRs and their target genes, providing biologically meaningful hypothesis embedded in their relationships. Twit Text FOAVip Discovery of Transcriptional Targets Regulated by Nuclear Receptors Using a Probabilistic Graphical Model ????Toxicol Sci http://www.kidney.de/pget.php?&tw=1&pmid=26643261 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26643261 #FOAvip English Wikipedia <ref>{{Cite pmid|26643261}}</ref> Discovery of Transcriptional Targets Regulated by Nuclear Receptors Using a Probabilistic Graphical Model #MMPMID26643261 Lee M; Huang R; Tong W Toxicol Sci 2016[Mar]; 150 (1): 64-73 PMID26643261show ga Nuclear receptors (NRs) are ligand-activated transcriptional regulators that play vital roles in key biological processes such as growth, differentiation, metabolism, reproduction, and morphogenesis. Disruption of NRs can result in adverse health effects such as NR-mediated endocrine disruption. A comprehensive understanding of core transcriptional targets regulated by NRs helps to elucidate their key biological processes in both toxicological and therapeutic aspects. In this study, we applied a probabilistic graphical model to identify the transcriptional targets of NRs and the biological processes they govern. The Tox21 program profiled a collection of approximate 10?000 environmental chemicals and drugs against a panel of human NRs in a quantitative high-throughput screening format for their NR disruption potential. The Japanese Toxicogenomics Project, one of the most comprehensive efforts in the field of toxicogenomics, generated large-scale gene expression profiles on the effect of 131 compounds (in its first phase of study) at various doses, and different durations, and their combinations. We applied author-topic model to these 2 toxicological datasets, which consists of 11 NRs run in either agonist and/or antagonist mode (18 assays total) and 203 in vitro human gene expression profiles connected by 52 shared drugs. As a result, a set of clusters (topics), which consists of a set of NRs and their associated target genes were determined. Various transcriptional targets of the NRs were identified by assays run in either agonist or antagonist mode. Our results were validated by functional analysis and compared with TRANSFAC data. In summary, our approach resulted in effective identification of associated/affected NRs and their target genes, providing biologically meaningful hypothesis embedded in their relationships. äDiscovery of Transcriptional Targets Regulated by Nuclear Receptors Us(epmc).pdf DeepDyve Pubget Overpricing