105 citations · 148 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 105 cited
Comprehensive evaluation of deep and graph learning on drug-drug interactions prediction
Xuan Lin, Lichang Dai, Yafang Zhou +9
Recent advances and achievements of artificial intelligence (AI) as well as deep and graph learning models have established their usefulness in biomedical applications, especially…
q-bio.BM2022★ 11 cited
Deep learning for drug repurposing: methods, databases, and applications
Xiaoqin Pan, Xuan Lin, Dongsheng Cao +5
Drug development is time-consuming and expensive. Repurposing existing drugs for new therapies is an attractive solution that accelerates drug development at reduced experimental c…
cs.LG2020★ 32 cited
DeepGS: Deep Representation Learning of Graphs and Sequences for Drug-Target Binding Affinity Prediction
Xuan Lin
Accurately predicting drug-target binding affinity (DTA) in silico is a key task in drug discovery. Most of the conventional DTA prediction methods are simulation-based, which rely…