Integrating supercomputing and artificial intelligence for life science.
basic_science · Level V
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- Record sourced from PubMed, PMID 36569549.
- Also identified by DOI 10.1016/j.patter.2022.100653 and PMC identifier 9768675.
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Abstract
Jiahua Rao and Shuangjia Zheng are Ph.D. students in Prof. Yang's lab (Supercomputing And AI for Life science, SAIL Lab) at Sun Yat-sen University. They recently developed an interpretable framework to quantitatively assess the interpretability of Graph Neural Network (GNN) and made comparison with medicinal chemists. Their meaningful benchmarking and rigorous framework would greatly benefit development of new interpretable methods in GNNs.