Dual-dropout graph convolutional network for predicting synthetic lethality in human cancers

• Main Authors: CAI, Ruichu, CHEN, Xuexin, FANG, Yuan, WU, Min, HAO, Yuexing
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: synthetic lethality; graph convolutional networks; dual dropout; Databases and Information Systems; OS and Networks
• Online Access: https://ink.library.smu.edu.sg/sis_research/5127; https://ink.library.smu.edu.sg/context/sis_research/article/6130/viewcontent/BIOINFO20_DDGCN_av.pdf
• Institution: Singapore Management University

Motivation: Synthetic lethality (SL) is a promising form of gene interaction for cancer therapy, as it is able to identify specific genes to target at cancer cells without disrupting normal cells. As high-throughput wet-lab settings are often costly and face various challenges, computational approac...