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ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases.
Wang, Wenjing; Zhang, Peng; Li, Leijie; Chen, Zhaobin; Bai, Weiyang; Liu, Guiyou; Zhang, Liangcai; Jia, Haiyang; Li, Li; Yu, Yingcui; Liao, Mingzhi.
Afiliación
  • Wang W; College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
  • Zhang P; School of Medicine, Tongji University, Shanghai, China.
  • Li L; College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
  • Chen Z; College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
  • Bai W; College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
  • Liu G; College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
  • Zhang L; School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
  • Jia H; School of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
  • Li L; Department of Statistics, Rice University, Houston, TX, USA.
  • Yu Y; College of Computer Science and Technology, Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, China.
  • Liao M; School of Medicine, Tongji University, Shanghai, China.
Database (Oxford) ; 20182018 01 01.
Article en En | MEDLINE | ID: mdl-30239683
ABSTRACT
Autophagy is the natural, regulated, destructive mechanism of the eukaryotes cell that disassembles unnecessary or dysfunctional components. In recent years, the association between autophagy and diseases has attracted more and more attention, but our understanding of the molecular mechanism about the association in the system perspective is limited and ambiguous. Hence, we developed the comprehensive bioinformatics resource Autophagy To Disease (ATD, http//auto2disease.nwsuaflmz.com) to archive autophagy-associated diseases. This resource provides bioinformatics annotation system about genes and chemicals about autophagy and human diseases by extracting results from previous studies with text mining technology. Based on the big data from ATD, we found that some classes of disease tend to be related with autophagy, including respiratory disease, cancer, urogenital disease and digestive system disease. We also found that some classes of autophagy-related diseases have a strong association among each other and constitute modules. Furthermore, we extracted the autophagy-disease-related genes (ADGs) from ATD and provided a novel algorithm Optimized Random Forest with Label model to predict potential ADGs. This bioinformatics annotation system about autophagy and human diseases may provide a basic resource for the further detection of the molecular mechanisms of autophagy pathway to disease.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Autofagia / Enfermedad / Biología Computacional Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Database (Oxford) Año: 2018 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Autofagia / Enfermedad / Biología Computacional Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Database (Oxford) Año: 2018 Tipo del documento: Article País de afiliación: China
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