ARN: analysis and prediction by adipogenic professional database. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Huang, Yan; Wang, Li; Zan, and
• Is Part Of: BMC systems biology. Volume 10:Issue 1(2016)
• Page Start: 1
• Page End: 12
• Publication Date: 2016-12
• Subjects: Adipogenesis -- Regulation -- Database -- Analysis; Biological systems -- Periodicals; Biology -- Research -- Periodicals; Cell physiology -- Periodicals; Genes -- Analysis -- Periodicals; 571
• DOI: 10.1186/s12918-016-0321-0
• Languages: English
• ISSNs: 1752-0509

Abstract

Abstract Adipogenesis is the process of cell differentiation by which mesenchymal stem cells become adipocytes. Extensive research is ongoing to identify genes, their protein products, and microRNAs that correlate with fat cell development. The existing databases have focused on certain types of regulatory factors and interactions. However, there is no relationship between the results of the experimental studies on adipogenesis and these databases because of the lack of an information center. This information fragmentation hampers the identification of key regulatory genes and pathways. Thus, it is necessary to provide an information center that is quickly and easily accessible to researchers in this field. We selected and integrated data from eight external databases based on the results of text-mining, and constructed a publicly available database and web interface (URL:http://210.27.80.93/arn/ ), which contained 30873 records related to adipogenic differentiation. Then, we designed an online analysis tool to analyze the experimental data or form a scientific hypothesis about adipogenesis through Swanson's literature-based discovery process. Furthermore, we calculated the "Impact Factor" ("IF") value that reflects the importance of each node by counting the numbers of relation records, expression records, and prediction records for each node. This platform can support ongoing adipogenesis research and contribute to the discovery of key regulatory genes and pathways.