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10.1093/bioinformatics/btw511 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btw511 C5018380!5018380!27485446     free     free     free Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bioinformatics 2016 ; 32 (18): 2886-8 Nephropedia Template TP {{tp|p=27485446|t=2016. HiPub: translating PubMed and PMC texts to networks for knowledge discovery |pdf=|usr=}}{{27485446}} gab.com Text HiPub: translating PubMed and PMC texts to networks for knowledge discovery JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=27485446 #FOAvip Summary: We introduce HiPub, a seamless Chrome browser plug-in that automatically recognizes, annotates and translates biomedical entities from texts into networks for knowledge discovery. Using a combination of two different named-entity recognition resources, HiPub can recognize genes, proteins, diseases, drugs, mutations and cell lines in texts, and achieve high precision and recall. HiPub extracts biomedical entity-relationships from texts to construct context-specific networks, and integrates existing network data from external databases for knowledge discovery. It allows users to add additional entities from related articles, as well as user-defined entities for discovering new and unexpected entity-relationships. HiPub provides functional enrichment analysis on the biomedical entity network, and link-outs to external resources to assist users in learning new entities and relations.Availability and Implementation: HiPub and detailed user guide are available at http://hipub.korea.ac.kr.Contact:kangj@korea.ac.kr, aikchoon.tan@ucdenver.eduSupplementary information:Supplementary data are available at Bioinformatics online. Twit Text FOAVip HiPub: translating PubMed and PMC texts to networks for knowledge discovery ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=27485446 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27485446 #FOAvip English Wikipedia <ref>{{Cite pmid|27485446}}</ref> HiPub: translating PubMed and PMC texts to networks for knowledge discovery #MMPMID27485446 Lee K; Shin W; Kim B; Lee S; Choi Y; Kim S; Jeon M; Tan AC; Kang J Bioinformatics 2016[Sep]; 32 (18): 2886-8 PMID27485446show ga Summary: We introduce HiPub, a seamless Chrome browser plug-in that automatically recognizes, annotates and translates biomedical entities from texts into networks for knowledge discovery. Using a combination of two different named-entity recognition resources, HiPub can recognize genes, proteins, diseases, drugs, mutations and cell lines in texts, and achieve high precision and recall. HiPub extracts biomedical entity-relationships from texts to construct context-specific networks, and integrates existing network data from external databases for knowledge discovery. It allows users to add additional entities from related articles, as well as user-defined entities for discovering new and unexpected entity-relationships. HiPub provides functional enrichment analysis on the biomedical entity network, and link-outs to external resources to assist users in learning new entities and relations.Availability and Implementation: HiPub and detailed user guide are available at http://hipub.korea.ac.kr.Contact:kangj@korea.ac.kr, aikchoon.tan@ucdenver.eduSupplementary information:Supplementary data are available at Bioinformatics online. äHiPub: translating PubMed and PMC texts to networks for knowledge disc(epmc).pdf DeepDyve Pubget Overpricing