TGPred: a tumor gene prediction webserver for analyzing structural and functional impacts of variants

• 作者: Jixiang Liu Quanxue Li Wei Liu Wentao Dai Xue-Ling Li Yuan-Yuan Li
• 来源期刊: 分子细胞生物学报（英文版）
• 年，卷（期）: 2020,（7）
• 所属期刊栏目: Application Note
• 页码范围: 556-558
• 页数: 3页
• 语种: 英文
• DOI: 10.1093/jmcb/mjaa007

摘要

With the increasing use of highthroughput sequencing technology in tumor research, a large number of somatic variations are being identified and some of them have proved to be responsible for tumorigenesis (Cancer Genome Atlas Research Network et al., 2013).Investigating structural and functional impacts of tumor somatic variants would greatly help to identify causal variations, understand the mechanisms of carcinogenesis, and develop novel anti-tumor therapies.Therefore, many efforts have recently been made to map genomic variations to 3D protein structure, such as G23D (Solomon et al., 2016) and G2S (Wang et al., 2018).