ENCD: a manually curated database of experimentally supported endocrine system disease and lncRNA associations

Author:

Hao Ming,Qi Yue1,Xu Rongji1,Zhao Kangqi2,Li Mingqing2,Shan Yongyan2,Xia Tian2,Yang Kun2,Hasi Wuyang2,Zhang Cong2,Li Daowei2,Wang Yi2,Wang Peng12ORCID,Kuang Hongyu2

Affiliation:

1. College of Bioinformatics Science and Technology, Harbin Medical University , 194 Xuefu Road, Harbin 150081, China

2. Department of Endocrinology, The First Affiliated Hospital of Harbin Medical University , 23 Youzheng Road, Harbin 150081, China

Abstract

Abstract ENCD (http://www.bio-server.cn/ENCD/) is a manually curated database that provides comprehensive experimentally supported associations among endocrine system diseases (ESDs) and long non-coding ribonucleic acid (lncRNAs). The incidence of ESDs has increased in recent years, often accompanying other chronic diseases, and can lead to disability. A growing body of research suggests that lncRNA plays an important role in the progression and metastasis of ESDs. However, there are no resources focused on collecting and integrating the latest and experimentally supported lncRNA–ESD associations. Hence, we developed an ENCD database that consists of 1379 associations between 35 ESDs and 501 lncRNAs in 12 human tissues curated from literature. By using ENCD, users can explore the genetic data for diseases corresponding to the body parts of interest as well as study the lncRNA regulating mechanism for ESDs. ENCD also provides a flexible tool to visualize a disease- or gene-centric regulatory network. In addition, ENCD offers a submission page for researchers to submit their newly discovered endocrine disorders-genetic data entries online. Collectively, ENCD will provide comprehensive insights for investigating the ESDs associated with lncRNAs. Database URL http://www.bio-server.cn/ENCD

Funder

National Natural Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Information Systems

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