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#artificial intelligence Preprint Sep 2026

AmbiModBench: Benchmarking Gene Perturbation Prediction Beyond Shared Responses

Predicting cellular responses to genetic perturbations helps prioritize experiments in single-cell genomics, where exhaustive measurement is infeasible. While computational models increasingly predict these responses, three evaluation deficiencies obscure what their scores demonstrate. First, absolute metrics cannot se...

Si-Kai Huang, Zhi-Wen Yang, Kai Yu et al. · 0 citations
Preprint Aug 2026

BioM-JEPA: joint-embedding prediction of graph-connected gene blocks in single cells

Results support graph-connected gene blocks as useful prediction units for JEPA-style representation learning in single-cell biology by supporting block-level prediction of graph-connected gene blocks defined by protein-association and corpus-derived coexpression evidence.

Yu-Hao Wang, Ze-Lin Zang, Yuxuan Liu et al. · 0 citations

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