Please use this identifier to cite or link to this item: https://doi.org/10.1093/database/baaa052
Title: Autophagy and Tumor Database: ATdb, a novel database connecting autophagy and tumor
Authors: Chen, K.
Yang, D.
Zhao, F.
Wang, S.
Ye, Y.
Sun, W.
Lu, H.
Ruan, Z.
Xu, J.
Wang, T.
Lu, G. 
Wang, L. 
Shi, Y.
Zhang, H.
Wu, H.
Lu, W.
Shen, Han-Ming 
Xia, D.
Wu, Y.
Issue Date: 2020
Publisher: Oxford University Press
Citation: Chen, K., Yang, D., Zhao, F., Wang, S., Ye, Y., Sun, W., Lu, H., Ruan, Z., Xu, J., Wang, T., Lu, G., Wang, L., Shi, Y., Zhang, H., Wu, H., Lu, W., Shen, Han-Ming, Xia, D., Wu, Y. (2020). Autophagy and Tumor Database: ATdb, a novel database connecting autophagy and tumor. Database 2020 : baaa052. ScholarBank@NUS Repository. https://doi.org/10.1093/database/baaa052
Rights: Attribution 4.0 International
Abstract: Autophagy is an essential cellular process that is closely implicated in diverse pathophysiological processes and a variety of human diseases, especially tumors. Autophagy is regarded as not only an anti-cancer process in tumorigenesis but also a pro-tumor process in progression and metastasis according to current research. It means the role of autophagy in tumor is considered to be complex, controversial and context dependent. Hence, a comprehensive database is of great significance to obtain an in-depth understanding of such complex correlations between autophagy and tumor. To achieve this objective, here we developed the Autophagy and Tumor Database (named as ATdb, http://www.bigzju.com/ATdb/#/) to compile the published information concerning autophagy and tumor research. ATdb connected 25 types of tumors with 137 genes required for autophagy-related pathways, containing 219 population filters, 2650 hazard ratio trend plots, 658 interacting microRNAs, 266 interacting long non-coding RNAs, 155 post-translational modifications, 298 DNA methylation records, 331 animal models and 70 clinical trials. ATdb could enable users to search, browse, download and carry out efficient online analysis. For instance, users can make prediction of autophagy gene regulators in a context-dependent manner and in a precise subpopulation and tumor subtypes. Also, it is feasible in ATdb to cluster tumors into distinguished groups based on the gene-related long non-coding RNAs to gain novel insights into their potential functional implications. Thus, ATdb offers a powerful online database for the autophagy community to explore the complex world of autophagy and tumor. Database URL: http://www.bigzju.com/ATdb/#/ © 2020 The Author(s) 2020. Published by Oxford University Press.
Source Title: Database
URI: https://scholarbank.nus.edu.sg/handle/10635/197797
ISSN: 17580463
DOI: 10.1093/database/baaa052
Rights: Attribution 4.0 International
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