DELPHAI predicts heterogeneous perturbation responses with learned cell fitness and gene-space retrieval

Authors

Zhang, X., Wu, H., Liu, H.

Abstract

Modelling heterogeneous cellular responses to perturbation holds the promise of scalable in silico screening and mechanistic insight. However, mass conservation despite cell-type-specific depletion, and lossy projections from gene space to latent space, hinder performance of state-of-the-art methods. DELPHAI, with learned per-cell-fitness filtering out depleted cells and gene-space retrieval bypassing the latent bottleneck, outperforms all baseline methods across two benchmark frameworks and offers explainability with inferred cell-type-specific survival without any biological priors.

Preprint server: bioRxiv
The authors list and abstract were imported from bioRxiv on 07 Jul 2026.

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