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CABA-Bind: Confounder-aligned backdoor adjustment for debiased RNA-ligand binding prediction.
CABA-Bind improves the reliability and ligand-specific interpretability of RNA-ligand molecular recognition modeling, and provided computational evidence suggesting that model-highlighted RNA regions around G17 and A53/A54 may contribute to ligand-associated recognition.
A multi-scale graph frequency network for structural and functional region analysis in spatial transcriptomics
E evaluation across diverse biological systems shows that SGFN achieves improved or competitive performance relative to representative baseline methods in reference-based benchmarks, and identifies biologically coherent spatial or functional regions in unlabeled datasets supported by marker-gene, spatial-autocorrelation, cell-type-colocalization, and pathway-enrichment evidence.