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10.1093/nar/gkab1048 http://scihub22266oqcxt.onion/10.1093/nar/gkab1048 34747468!8728227!34747468     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       Nucleic+Acids+Res 2022 ; 50 (D1): D632-D639 Nephropedia Template TP {{tp|p=34747468|t=2022. HumanNet v3: an improved database of human gene networks for disease research |pdf=|usr=}}{{34747468}} gab.com Text HumanNet v3: an improved database of human gene networks for disease research JO: Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34747468 #FOAvip Network medicine has proven useful for dissecting genetic organization of complex human diseases. We have previously published HumanNet, an integrated network of human genes for disease studies. Since the release of the last version of HumanNet, many large-scale protein-protein interaction datasets have accumulated in public depositories. Additionally, the numbers of research papers and functional annotations for gene-phenotype associations have increased significantly. Therefore, updating HumanNet is a timely task for further improvement of network-based research into diseases. Here, we present HumanNet v3 (https://www.inetbio.org/humannet/, covering 99.8% of human protein coding genes) constructed by means of the expanded data with improved network inference algorithms. HumanNet v3 supports a three-tier model: HumanNet-PI (a protein-protein physical interaction network), HumanNet-FN (a functional gene network), and HumanNet-XC (a functional network extended by co-citation). Users can select a suitable tier of HumanNet for their study purpose. We showed that on disease gene predictions, HumanNet v3 outperforms both the previous HumanNet version and other integrated human gene networks. Furthermore, we demonstrated that HumanNet provides a feasible approach for selecting host genes likely to be associated with COVID-19. Twit Text FOAVip HumanNet v3: an improved database of human gene networks for disease research ????Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34747468 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34747468 #FOAvip English Wikipedia <ref>{{Cite pmid|34747468}}</ref> HumanNet v3: an improved database of human gene networks for disease research #MMPMID34747468 Kim CY; Baek S; Cha J; Yang S; Kim E; Marcotte EM; Hart T; Lee I Nucleic Acids Res 2022[Jan]; 50 (D1): D632-D639 PMID34747468show ga Network medicine has proven useful for dissecting genetic organization of complex human diseases. We have previously published HumanNet, an integrated network of human genes for disease studies. Since the release of the last version of HumanNet, many large-scale protein-protein interaction datasets have accumulated in public depositories. Additionally, the numbers of research papers and functional annotations for gene-phenotype associations have increased significantly. Therefore, updating HumanNet is a timely task for further improvement of network-based research into diseases. Here, we present HumanNet v3 (https://www.inetbio.org/humannet/, covering 99.8% of human protein coding genes) constructed by means of the expanded data with improved network inference algorithms. HumanNet v3 supports a three-tier model: HumanNet-PI (a protein-protein physical interaction network), HumanNet-FN (a functional gene network), and HumanNet-XC (a functional network extended by co-citation). Users can select a suitable tier of HumanNet for their study purpose. We showed that on disease gene predictions, HumanNet v3 outperforms both the previous HumanNet version and other integrated human gene networks. Furthermore, we demonstrated that HumanNet provides a feasible approach for selecting host genes likely to be associated with COVID-19. |*Algorithms[MESH] |*Databases, Genetic[MESH] |*Gene Regulatory Networks[MESH] |*Software[MESH] |COVID-19/*genetics/virology[MESH] |Communicable Diseases/classification/*genetics[MESH] |Gene Ontology[MESH] |Humans[MESH] |Internet[MESH] |Molecular Sequence Annotation[MESH] |Protein Interaction Mapping[MESH]HumanNet v3: an improved database of human gene networks for disease r(epmc).pdf DeepDyve Pubget Overpricing