Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1186/s12859-016-1447-1 http://scihub22266oqcxt.onion/10.1186/s12859-016-1447-1 C5333168!5333168!28251874     free     free     free 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 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 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       BMC+Bioinformatics 2017 ; 18 (Suppl 2): ä Nephropedia Template TP {{tp|p=28251874|t=2017. PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space |pdf=|usr=}}{{28251874}} gab.com Text PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space JO: BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=28251874 #FOAvip Background: Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists? understanding of phenotypic behavior associated with specific genes. Results: We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks. Conclusions: We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases. Electronic supplementary material: The online version of this article (doi:10.1186/s12859-016-1447-1) contains supplementary material, which is available to authorized users. Twit Text FOAVip PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space ????BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=28251874 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28251874 #FOAvip English Wikipedia <ref>{{Cite pmid|28251874}}</ref> PRODIGEN: visualizing the probability landscape of stochastic gene regulatory networks in state and time space #MMPMID28251874 Ma C; Luciani T; Terebus A; Liang J; Marai GE BMC Bioinformatics 2017[]; 18 (Suppl 2): ä PMID28251874show ga Background: Visualizing the complex probability landscape of stochastic gene regulatory networks can further biologists? understanding of phenotypic behavior associated with specific genes. Results: We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based visual analysis tool for the systematic exploration of probability distributions over simulation time and state space in such networks. PRODIGEN was designed in collaboration with bioinformaticians who research stochastic gene networks. The analysis tool combines in a novel way existing, expanded, and new visual encodings to capture the time-varying characteristics of probability distributions: spaghetti plots over one dimensional projection, heatmaps of distributions over 2D projections, enhanced with overlaid time curves to display temporal changes, and novel individual glyphs of state information corresponding to particular peaks. Conclusions: We demonstrate the effectiveness of the tool through two case studies on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network. Domain expert feedback indicates that our visual approach can help biologists: 1) visualize probabilities of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks in the probability landscape that have potential relation to specific diseases. Electronic supplementary material: The online version of this article (doi:10.1186/s12859-016-1447-1) contains supplementary material, which is available to authorized users. äPRODIGEN: visualizing the probability landscape of stochastic gene reg(epmc).pdf DeepDyve Pubget Overpricing