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10.1186/1752-0509-7-S6-S18 http://scihub22266oqcxt.onion/10.1186/1752-0509-7-S6-S18 C4029543!4029543!24565527     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       BMC+Syst+Biol 2013 ; 7 (Suppl 6): S18 Nephropedia Template TP {{tp|p=24565527|t=2013. Inferring protein domains associated with drug side effects based on drug-target interaction network |pdf=|usr=}}{{24565527}} gab.com Text Inferring protein domains associated with drug side effects based on drug-target interaction network JO: BMC Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=24565527 #FOAvip Background: Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. Results: In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. Conclusion: The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains. Twit Text FOAVip Inferring protein domains associated with drug side effects based on drug-target interaction network ????BMC Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=24565527 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24565527 #FOAvip English Wikipedia <ref>{{Cite pmid|24565527}}</ref> Inferring protein domains associated with drug side effects based on drug-target interaction network #MMPMID24565527 Iwata H; Mizutani S; Tabei Y; Kotera M; Goto S; Yamanishi Y BMC Syst Biol 2013[]; 7 (Suppl 6): S18 PMID24565527show ga Background: Most phenotypic effects of drugs are involved in the interactions between drugs and their target proteins, however, our knowledge about the molecular mechanism of the drug-target interactions is very limited. One of challenging issues in recent pharmaceutical science is to identify the underlying molecular features which govern drug-target interactions. Results: In this paper, we make a systematic analysis of the correlation between drug side effects and protein domains, which we call "pharmacogenomic features," based on the drug-target interaction network. We detect drug side effects and protein domains that appear jointly in known drug-target interactions, which is made possible by using classifiers with sparse models. It is shown that the inferred pharmacogenomic features can be used for predicting potential drug-target interactions. We also discuss advantages and limitations of the pharmacogenomic features, compared with the chemogenomic features that are the associations between drug chemical substructures and protein domains. Conclusion: The inferred side effect-domain association network is expected to be useful for estimating common drug side effects for different protein families and characteristic drug side effects for specific protein domains. äInferring protein domains associated with drug side effects based on d(epmc).pdf DeepDyve Pubget Overpricing