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10.1186/s12967-016-1078-3 http://scihub22266oqcxt.onion/10.1186/s12967-016-1078-3 C5120462!5120462!27876057     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=27876057&cmd=llinks): Failed to open stream: HTTP request failed! 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Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research |pdf=|usr=}}{{27876057}} gab.com Text Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research JO: J Transl Med http://www.kidney.de/pget.php?&tw=1&pmid=27876057 #FOAvip With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians? point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world?s major diseases. Twit Text FOAVip Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research ????J Transl Med http://www.kidney.de/pget.php?&tw=1&pmid=27876057 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27876057 #FOAvip English Wikipedia <ref>{{Cite pmid|27876057}}</ref> Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research #MMPMID27876057 Jinawath N; Bunbanjerdsuk S; Chayanupatkul M; Ngamphaiboon N; Asavapanumas N; Svasti J; Charoensawan V J Transl Med 2016[]; 14 (ä): ä PMID27876057show ga With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians? point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world?s major diseases. äBridging the gap between clinicians and systems biologists: from netwo(epmc).pdf DeepDyve Pubget Overpricing