ATD: a comprehensive bioinformatics resource for deciphering the association of autophagy and diseases. (18th September 2018)

• Record Type: Journal Article
• Authors: Wang, Wenjing; Zhang, Peng; Li, Leijie; Chen, Zhaobin; Bai, Weiyang; Liu, Guiyou; Zhang, Liangcai; Jia, Haiyang; Li, Li; Yu, Yingcui; Liao, Mingzhi
• Is Part Of: Database. Volume 2018(2018)
• Publication Date: 2018-09-18
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/bay093
• Languages: English
• ISSNs: 1758-0463

Abstract

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.