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10.1186/s13637-017-0059-z http://scihub22266oqcxt.onion/10.1186/s13637-017-0059-z C5359264/?report=reader!5359264!28477207     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28477207&cmd=llinks): Failed to open stream: HTTP request failed! 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From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data |pdf=|usr=}}{{28477207}} gab.com Text From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data JO: EURASIP J Bioinform Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=28477207 #FOAvip The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis. Twit Text FOAVip From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data ????EURASIP J Bioinform Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=28477207 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28477207 #FOAvip English Wikipedia <ref>{{Cite pmid|28477207}}</ref> From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data #MMPMID28477207 Vella D; Zoppis I; Mauri G; Mauri P; Di Silvestre D EURASIP J Bioinform Syst Biol 2017[Dec]; 2017 (ä): ä PMID28477207show ga The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis. äFrom protein-protein interactions to protein co-expression networks: a(epmc).pdf DeepDyve Pubget Overpricing