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10.1186/1752-0509-9-S6-S5 http://scihub22266oqcxt.onion/10.1186/1752-0509-9-S6-S5 C4674859!4674859!26679379     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26679379&cmd=llinks): Failed to open stream: HTTP request failed! 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Constructing a molecular interaction network for thyroid cancer via large-scale text mining of gene and pathway events |pdf=|usr=}}{{26679379}} gab.com Text Constructing a molecular interaction network for thyroid cancer via large-scale text mining of gene and pathway events JO: BMC Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=26679379 #FOAvip Background: Biomedical studies need assistance from automated tools and easily accessible data to address the problem of the rapidly accumulating literature. Text-mining tools and curated databases have been developed to address such needs and they can be applied to improve the understanding of molecular pathogenesis of complex diseases like thyroid cancer. Results: We have developed a system, PWTEES, which extracts pathway interactions from the literature utilizing an existing event extraction tool (TEES) and pathway named entity recognition (PathNER). We then applied the system on a thyroid cancer corpus and systematically extracted molecular interactions involving either genes or pathways. With the extracted information, we constructed a molecular interaction network taking genes and pathways as nodes. Using curated pathway information and network topological analyses, we highlight key genes and pathways involved in thyroid carcinogenesis. Conclusions: Mining events involving genes and pathways from the literature and integrating curated pathway knowledge can help improve the understanding of molecular interactions of complex diseases. The system developed for this study can be applied in studies other than thyroid cancer. The source code is freely available online at https://github.com/chengkun-wu/PWTEES. Twit Text FOAVip Constructing a molecular interaction network for thyroid cancer via large-scale text mining of gene and pathway events ????BMC Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=26679379 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26679379 #FOAvip English Wikipedia <ref>{{Cite pmid|26679379}}</ref> Constructing a molecular interaction network for thyroid cancer via large-scale text mining of gene and pathway events #MMPMID26679379 Wu C; Schwartz JM; Brabant G; Peng SL; Nenadic G BMC Syst Biol 2015[]; 9 (Suppl 6): S5 PMID26679379show ga Background: Biomedical studies need assistance from automated tools and easily accessible data to address the problem of the rapidly accumulating literature. Text-mining tools and curated databases have been developed to address such needs and they can be applied to improve the understanding of molecular pathogenesis of complex diseases like thyroid cancer. Results: We have developed a system, PWTEES, which extracts pathway interactions from the literature utilizing an existing event extraction tool (TEES) and pathway named entity recognition (PathNER). We then applied the system on a thyroid cancer corpus and systematically extracted molecular interactions involving either genes or pathways. With the extracted information, we constructed a molecular interaction network taking genes and pathways as nodes. Using curated pathway information and network topological analyses, we highlight key genes and pathways involved in thyroid carcinogenesis. Conclusions: Mining events involving genes and pathways from the literature and integrating curated pathway knowledge can help improve the understanding of molecular interactions of complex diseases. The system developed for this study can be applied in studies other than thyroid cancer. The source code is freely available online at https://github.com/chengkun-wu/PWTEES. äConstructing a molecular interaction network for thyroid cancer via la(epmc).pdf DeepDyve Pubget Overpricing