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iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research

Current pharmacogenetic studies have obtained many genetic models that can predict the therapeutic efficacy of anticancer drugs. Although some of these models are of crucial importance and have been used in clinical practice, these very valuable models have not been well adopted into cancer research...

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Detalles Bibliográficos
Autores principales: Chen, Xiang, Guo, Yi, Chen, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646137/
https://www.ncbi.nlm.nih.gov/pubmed/32916316
http://dx.doi.org/10.1016/j.gpb.2019.11.011
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author Chen, Xiang
Guo, Yi
Chen, Xin
author_facet Chen, Xiang
Guo, Yi
Chen, Xin
author_sort Chen, Xiang
collection PubMed
description Current pharmacogenetic studies have obtained many genetic models that can predict the therapeutic efficacy of anticancer drugs. Although some of these models are of crucial importance and have been used in clinical practice, these very valuable models have not been well adopted into cancer research to promote the development of cancer therapies due to the lack of integration and standards for the existing data of the pharmacogenetic studies. For this purpose, we built a resource investigating genetic model of drug response (iGMDR), which integrates the models from in vitro and in vivo pharmacogenetic studies with different omics data from a variety of technical systems. In this study, we introduced a standardized process for all integrations, and described how users can utilize these models to gain insights into cancer. iGMDR is freely accessible at https://igmdr.modellab.cn.
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spelling pubmed-76461372020-11-13 iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research Chen, Xiang Guo, Yi Chen, Xin Genomics Proteomics Bioinformatics Database Current pharmacogenetic studies have obtained many genetic models that can predict the therapeutic efficacy of anticancer drugs. Although some of these models are of crucial importance and have been used in clinical practice, these very valuable models have not been well adopted into cancer research to promote the development of cancer therapies due to the lack of integration and standards for the existing data of the pharmacogenetic studies. For this purpose, we built a resource investigating genetic model of drug response (iGMDR), which integrates the models from in vitro and in vivo pharmacogenetic studies with different omics data from a variety of technical systems. In this study, we introduced a standardized process for all integrations, and described how users can utilize these models to gain insights into cancer. iGMDR is freely accessible at https://igmdr.modellab.cn. Elsevier 2020-04 2020-09-08 /pmc/articles/PMC7646137/ /pubmed/32916316 http://dx.doi.org/10.1016/j.gpb.2019.11.011 Text en © 2020 The Authors. Published by Elsevier B.V. and Science Press on behalf of Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Database
Chen, Xiang
Guo, Yi
Chen, Xin
iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research
title iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research
title_full iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research
title_fullStr iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research
title_full_unstemmed iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research
title_short iGMDR: Integrated Pharmacogenetic Resource Guide to Cancer Therapy and Research
title_sort igmdr: integrated pharmacogenetic resource guide to cancer therapy and research
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7646137/
https://www.ncbi.nlm.nih.gov/pubmed/32916316
http://dx.doi.org/10.1016/j.gpb.2019.11.011
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