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10.1093/bioinformatics/btu403 http://scihub22266oqcxt.onion/10.1093/bioinformatics/btu403 C4184255!4184255!24974205     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bioinformatics 2014 ; 30 (20): 2923-30 Nephropedia Template TP {{tp|p=24974205|t=2014. Drug repositioning by integrating target information through a heterogeneous network model |pdf=|usr=}}{{24974205}} gab.com Text Drug repositioning by integrating target information through a heterogeneous network model JO: Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24974205 #FOAvip Motivation: The emergence of network medicine not only offers more opportunities for better and more complete understanding of the molecular complexities of diseases, but also serves as a promising tool for identifying new drug targets and establishing new relationships among diseases that enable drug repositioning. Computational approaches for drug repositioning by integrating information from multiple sources and multiple levels have the potential to provide great insights to the complex relationships among drugs, targets, disease genes and diseases at a system level.Results: In this article, we have proposed a computational framework based on a heterogeneous network model and applied the approach on drug repositioning by using existing omics data about diseases, drugs and drug targets. The novelty of the framework lies in the fact that the strength between a disease?drug pair is calculated through an iterative algorithm on the heterogeneous graph that also incorporates drug-target information. Comprehensive experimental results show that the proposed approach significantly outperforms several recent approaches. Case studies further illustrate its practical usefulness.Availability and implementation:http://cbc.case.eduContact:jingli@cwru.eduSupplementary information:Supplementary data are available at Bioinformatics online. Twit Text FOAVip Drug repositioning by integrating target information through a heterogeneous network model ????Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=24974205 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24974205 #FOAvip English Wikipedia <ref>{{Cite pmid|24974205}}</ref> Drug repositioning by integrating target information through a heterogeneous network model #MMPMID24974205 Wang W; Yang S; Zhang X; Li J Bioinformatics 2014[Oct]; 30 (20): 2923-30 PMID24974205show ga Motivation: The emergence of network medicine not only offers more opportunities for better and more complete understanding of the molecular complexities of diseases, but also serves as a promising tool for identifying new drug targets and establishing new relationships among diseases that enable drug repositioning. Computational approaches for drug repositioning by integrating information from multiple sources and multiple levels have the potential to provide great insights to the complex relationships among drugs, targets, disease genes and diseases at a system level.Results: In this article, we have proposed a computational framework based on a heterogeneous network model and applied the approach on drug repositioning by using existing omics data about diseases, drugs and drug targets. The novelty of the framework lies in the fact that the strength between a disease?drug pair is calculated through an iterative algorithm on the heterogeneous graph that also incorporates drug-target information. Comprehensive experimental results show that the proposed approach significantly outperforms several recent approaches. Case studies further illustrate its practical usefulness.Availability and implementation:http://cbc.case.eduContact:jingli@cwru.eduSupplementary information:Supplementary data are available at Bioinformatics online. äDrug repositioning by integrating target information through a heterog(epmc).pdf DeepDyve Pubget Overpricing