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DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal
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 upda...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218202/ https://www.ncbi.nlm.nih.gov/pubmed/34060634 http://dx.doi.org/10.1093/nar/gkab438 |
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author | Zheng, Shuyu Aldahdooh, Jehad Shadbahr, Tolou Wang, Yinyin Aldahdooh, Dalal Bao, Jie Wang, Wenyu Tang, Jing |
author_facet | Zheng, Shuyu Aldahdooh, Jehad Shadbahr, Tolou Wang, Yinyin Aldahdooh, Dalal Bao, Jie Wang, Wenyu Tang, Jing |
author_sort | Zheng, Shuyu |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8218202 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82182022021-06-22 DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal Zheng, Shuyu Aldahdooh, Jehad Shadbahr, Tolou Wang, Yinyin Aldahdooh, Dalal Bao, Jie Wang, Wenyu Tang, Jing Nucleic Acids Res Web Server Issue 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. Oxford University Press 2021-06-01 /pmc/articles/PMC8218202/ /pubmed/34060634 http://dx.doi.org/10.1093/nar/gkab438 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Web Server Issue Zheng, Shuyu Aldahdooh, Jehad Shadbahr, Tolou Wang, Yinyin Aldahdooh, Dalal Bao, Jie Wang, Wenyu Tang, Jing DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal |
title | DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal |
title_full | DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal |
title_fullStr | DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal |
title_full_unstemmed | DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal |
title_short | DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal |
title_sort | drugcomb update: a more comprehensive drug sensitivity data repository and analysis portal |
topic | Web Server Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8218202/ https://www.ncbi.nlm.nih.gov/pubmed/34060634 http://dx.doi.org/10.1093/nar/gkab438 |
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