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10.1093/nar/gkab438 http://scihub22266oqcxt.onion/10.1093/nar/gkab438 34060634!8218202!34060634     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 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Nucleic+Acids+Res 2021 ; 49 (W1): W174-W184 Nephropedia Template TP {{tp|p=34060634|t=2021. DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal |pdf=|usr=}}{{34060634}} gab.com Text DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal JO: Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34060634 #FOAvip Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here, we report significant updates of DrugComb, including: (i) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; (ii) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; (iii) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample and (iv) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases. Twit Text FOAVip DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal ????Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34060634 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34060634 #FOAvip English Wikipedia <ref>{{Cite pmid|34060634}}</ref> DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal #MMPMID34060634 Zheng S; Aldahdooh J; Shadbahr T; Wang Y; Aldahdooh D; Bao J; Wang W; Tang J Nucleic Acids Res 2021[Jul]; 49 (W1): W174-W184 PMID34060634show ga Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here, we report significant updates of DrugComb, including: (i) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; (ii) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; (iii) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample and (iv) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases. |*Algorithms[MESH] |*Databases, Factual[MESH] |*Drug Evaluation, Preclinical[MESH] |*Drug Therapy, Combination[MESH] |*Internet[MESH] |COVID-19 Drug Treatment[MESH] |Data Visualization[MESH] |Datasets as Topic[MESH] |Drug Synergism[MESH] |Hemorrhagic Fever, Ebola/drug therapy[MESH] |Humans[MESH] |Machine Learning[MESH] |Malaria/drug therapy[MESH]DrugComb update: a more comprehensive drug sensitivity data repository(epmc).pdf DeepDyve Pubget Overpricing