RadAtlas 1.0: a knowledgebase focusing on radiation-associated genes. (2nd August 2020)

• Record Type: Journal Article
• Authors: Xu, Hao; Liu, Yuan; Li, Yang; Diao, Lihong; Xun, Ziyu; Zhang, Yuqi; Wang, Zhidong; Li, Dong
• Is Part Of: International journal of radiation biology. Volume 96:Number 8(2020)
• Page Start: 980
• Page End: 987
• Publication Date: 2020-08-02
• Subjects: Ionizing radiation -- genes -- literature mining -- differentially expressed gene analysis; Radiation -- Physiological effect -- Periodicals; Radiobiology -- Periodicals; 571.45
• DOI: 10.1080/09553002.2020.1761567
• Languages: English
• ISSNs: 0955-3002

Abstract

Abstract: Purpose: Ionizing radiation has very complex biological effects, such as inducing damage to DNA and proteins, ionizing water molecules to produce toxic free radicals, and triggering genetic and somatic effects. Understanding the biomolecular response mechanism of radiation is very important for the prevention and treatment of radiation diseases. However, function information of these radiation-associated genes is hidden in numbers of scientific papers and databases, making it difficult to understand the response mechanism of ionizing radiation. Materials and methods: We collected radiation-associated genes by literature and database mining. Literature and database mining was performed on the basis of biomedical literature from PubMed and gene expression datasets from GEO respectively. Results: We built an ionizing radiation related knowledgebase RadAtlas 1.0 (http://biokb.ncpsb.org/radatlas ), which contains 598 radiation-associated genes compiled from literature mining, and 611 potential radiation-associated genes collected from gene expression datasets by differential gene expression analysis. We also provide a user-friendly web interface that offers multiple search methods. Conclusions: RadAtlas collected a large amount of information about genes, biological processes, and pathways related to ionizing radiation. It is the first attempt to provide a comprehensive catalog of radiation-associated genes with literature evidence and potential radiation-associated genes with differential expression evidence. We believe that RadAtlas would be a helpful tool to understand the response mechanism to ionizing radiation.