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10.1186/s12859-017-1945-9 http://scihub22266oqcxt.onion/10.1186/s12859-017-1945-9 29202689/?report=reader!5715631!29202689     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       BMC+Bioinformatics 2017 ; 18 (1): 536 Nephropedia Template TP {{tp|p=29202689|t=2017. Explorative visual analytics on interval-based genomic data and their metadata |pdf=|usr=}}{{29202689}} gab.com Text Explorative visual analytics on interval-based genomic data and their metadata JO: BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=29202689 #FOAvip BACKGROUND: With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. RESULTS: This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. CONCLUSIONS: GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSE under GPLv3 open-source license. Twit Text FOAVip Explorative visual analytics on interval-based genomic data and their metadata ????BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=29202689 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29202689 #FOAvip English Wikipedia <ref>{{Cite pmid|29202689}}</ref> Explorative visual analytics on interval-based genomic data and their metadata #MMPMID29202689 Jalili V; Matteucci M; Masseroli M; Ceri S BMC Bioinformatics 2017[Dec]; 18 (1): 536 PMID29202689show ga BACKGROUND: With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. RESULTS: This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. CONCLUSIONS: GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSE under GPLv3 open-source license. |*Databases, Genetic[MESH] |*Metadata[MESH] |A549 Cells[MESH] |Dexamethasone/pharmacology[MESH] |Ethanol/pharmacology[MESH] |Genomics/*methods[MESH] |Humans[MESH] |Models, Theoretical[MESH] |Pattern Recognition, Automated[MESH] |Protein Interaction Mapping[MESH]Explorative visual analytics on interval-based genomic data and their (epmc).pdf DeepDyve Pubget Overpricing