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10.1371/journal.pbio.1002303 http://scihub22266oqcxt.onion/10.1371/journal.pbio.1002303 C4658184!4658184 !26600012     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26600012 &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 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26600012 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       PLoS+Biol 2015 ; 13 (11 ): e1002303 Nephropedia Template TP {{tp|p=26600012 |t=2015. Computing Workflows for Biologists: A Roadmap |pdf=|usr=}}{{26600012 }} gab.com Text Computing Workflows for Biologists: A Roadmap JO: PLoS Biol http://www.kidney.de/pget.php?&tw=1&pmid=26600012 #FOAvip Extremely large datasets have become routine in biology. However, performing a computational analysis of a large dataset can be overwhelming, especially for novices. Here, we present a step-by-step guide to computing workflows with the biologist end-user in mind. Starting from a foundation of sound data management practices, we make specific recommendations on how to approach and perform computational analyses of large datasets, with a view to enabling sound, reproducible biological research. Twit Text FOAVip Computing Workflows for Biologists: A Roadmap ????PLoS Biol http://www.kidney.de/pget.php?&tw=1&pmid=26600012 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26600012 #FOAvip English Wikipedia <ref>{{Cite pmid|26600012 }}</ref> Computing Workflows for Biologists: A Roadmap #MMPMID26600012 Shade A ; Teal TK PLoS Biol 2015[]; 13 (11 ): e1002303 PMID26600012 show ga Extremely large datasets have become routine in biology. However, performing a computational analysis of a large dataset can be overwhelming, especially for novices. Here, we present a step-by-step guide to computing workflows with the biologist end-user in mind. Starting from a foundation of sound data management practices, we make specific recommendations on how to approach and perform computational analyses of large datasets, with a view to enabling sound, reproducible biological research. |*Biology/trends [MESH] |*Computing Methodologies [MESH] |*Workflow [MESH] |Animals [MESH] |Computational Biology/*methods/trends [MESH] |Database Management Systems/trends [MESH] |Datasets as Topic/trends [MESH] |Guidelines as Topic [MESH] |Humans [MESH] |Reproducibility of Results [MESH] |Terminology as Topic [MESH]Computing Workflows for Biologists: A Roadmap (epmc).pdf DeepDyve Pubget Overpricing