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10.1093/bioinformatics/btw007 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btw007 C5860402!5860402!26801959     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26801959&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bioinformatics 2016 ; 32 (10): 1509-17 Nephropedia Template TP {{tp|p=26801959|t=2016. Multi-task consensus clustering of genome-wide transcriptomes from related biological conditions |pdf=|usr=}}{{26801959}} gab.com Text Multi-task consensus clustering of genome-wide transcriptomes from related biological conditions JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=26801959 #FOAvip Motivation: Identifying the shared and pathogen-specific components of host transcriptional regulatory programs is important for understanding the principles of regulation of immune response. Recent efforts in systems biology studies of infectious diseases have resulted in a large collection of datasets measuring host transcriptional response to various pathogens. Computational methods to identify and compare gene expression modules across different infections offer a powerful way to identify strain-specific and shared components of the regulatory program. An important challenge is to identify statistically robust gene expression modules as well as to reliably detect genes that change their module memberships between infections.Results: We present MULCCH (MULti-task spectral Consensus Clustering for Hierarchically related tasks), a consensus extension of a multi-task clustering algorithm to infer high-confidence strain-specific host response modules under infections from multiple virus strains. On simulated data, MULCCH more accurately identifies genes exhibiting pathogen-specific patterns compared to non-consensus and nonmulti-task clustering approaches. Application of MULCCH to mammalian transcriptional response to a panel of influenza viruses showed that our method identifies clusters with greater coherence compared to non-consensus methods. Further, MULCCH derived clusters are enriched for several immune system-related processes and regulators. In summary, MULCCH provides a reliable module-based approach to identify molecular pathways and gene sets characterizing commonality and specificity of host response to viruses of different pathogenicities.Availability and implementation: The source code is available at https://bitbucket.org/roygroup/mulcchContact:sroy@biostat.wisc.eduSupplementary information:Supplementary data are available at Bioinformatics online. Twit Text FOAVip Multi-task consensus clustering of genome-wide transcriptomes from related biological conditions ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=26801959 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26801959 #FOAvip English Wikipedia <ref>{{Cite pmid|26801959}}</ref> Multi-task consensus clustering of genome-wide transcriptomes from related biological conditions #MMPMID26801959 Niu Z; Chasman D; Eisfeld AJ; Kawaoka Y; Roy S Bioinformatics 2016[May]; 32 (10): 1509-17 PMID26801959show ga Motivation: Identifying the shared and pathogen-specific components of host transcriptional regulatory programs is important for understanding the principles of regulation of immune response. Recent efforts in systems biology studies of infectious diseases have resulted in a large collection of datasets measuring host transcriptional response to various pathogens. Computational methods to identify and compare gene expression modules across different infections offer a powerful way to identify strain-specific and shared components of the regulatory program. An important challenge is to identify statistically robust gene expression modules as well as to reliably detect genes that change their module memberships between infections.Results: We present MULCCH (MULti-task spectral Consensus Clustering for Hierarchically related tasks), a consensus extension of a multi-task clustering algorithm to infer high-confidence strain-specific host response modules under infections from multiple virus strains. On simulated data, MULCCH more accurately identifies genes exhibiting pathogen-specific patterns compared to non-consensus and nonmulti-task clustering approaches. Application of MULCCH to mammalian transcriptional response to a panel of influenza viruses showed that our method identifies clusters with greater coherence compared to non-consensus methods. Further, MULCCH derived clusters are enriched for several immune system-related processes and regulators. In summary, MULCCH provides a reliable module-based approach to identify molecular pathways and gene sets characterizing commonality and specificity of host response to viruses of different pathogenicities.Availability and implementation: The source code is available at https://bitbucket.org/roygroup/mulcchContact:sroy@biostat.wisc.eduSupplementary information:Supplementary data are available at Bioinformatics online. äMulti-task consensus clustering of genome-wide transcriptomes from rel(epmc).pdf DeepDyve Pubget Overpricing