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GEAR: A database of Genomic Elements Associated with drug Resistance.
Wang, Yin-Ying; Chen, Wei-Hua; Xiao, Pei-Pei; Xie, Wen-Bin; Luo, Qibin; Bork, Peer; Zhao, Xing-Ming.
Afiliação
  • Wang YY; Department of Computer Science and Technology, Tongji University, Shanghai 201804, China.
  • Chen WH; Department of Electronic Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong.
  • Xiao PP; Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular-imaging, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology (HUST), Wuhan, Hubei 430074, Chin
  • Xie WB; Department of Computer Science and Technology, Tongji University, Shanghai 201804, China.
  • Luo Q; Department of Computer Science and Technology, Tongji University, Shanghai 201804, China.
  • Bork P; Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China.
  • Zhao XM; European Molecular Biology Laboratory (EMBL), Heidelberg, 69117, Germany.
Sci Rep ; 7: 44085, 2017 03 15.
Article em En | MEDLINE | ID: mdl-28294141
ABSTRACT
Drug resistance is becoming a serious problem that leads to the failure of standard treatments, which is generally developed because of genetic mutations of certain molecules. Here, we present GEAR (A database of Genomic Elements Associated with drug Resistance) that aims to provide comprehensive information about genomic elements (including genes, single-nucleotide polymorphisms and microRNAs) that are responsible for drug resistance. Right now, GEAR contains 1631 associations between 201 human drugs and 758 genes, 106 associations between 29 human drugs and 66 miRNAs, and 44 associations between 17 human drugs and 22 SNPs. These relationships are firstly extracted from primary literature with text mining and then manually curated. The drug resistome deposited in GEAR provides insights into the genetic factors underlying drug resistance. In addition, new indications and potential drug combinations can be identified based on the resistome. The GEAR database can be freely accessed through http//gear.comp-sysbio.org.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Resistência a Medicamentos / Bases de Dados Genéticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Resistência a Medicamentos / Bases de Dados Genéticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2017 Tipo de documento: Article