DeepEBV: a deep learning model to predict Epstein–Barr virus (EBV) integration sites

• Published in: Bioinformatics (Oxford, England) Vol. 37; no. 20; pp. 3405 - 3411
• Main Authors: Liang, Jiuxing, Cui, Zifeng, Wu, Canbiao, Yu, Yao, Tian, Rui, Xie, Hongxian, Jin, Zhuang, Fan, Weiwen, Xie, Weiling, Huang, Zhaoyue, Xu, Wei, Zhu, Jingjing, You, Zeshan, Guo, Xiaofang, Qiu, Xiaofan, Ye, Jiahao, Lang, Bin, Li, Mengyuan, Tan, Songwei, Hu, Zheng
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 25.10.2021

Abstract Motivation Epstein–Barr virus (EBV) is one of the most prevalent DNA oncogenic viruses. The integration of EBV into the host genome has been reported to play an important role in cancer development. The preference of EBV integration showed strong dependence on the local genomic environment,...