Bison
Cross-dataset model for globally unseen-compound response prediction using a shared gene representation, discrete diffusion models, and matched drug-contrast supervision.
- from
- Computational Biology
- added
- 2026-10-10
- likes
- 0
similar
-
-
CMonge github.com
Conditional optimal transport model for generalizable single-cell perturbation response prediction across drugs and doses.
-
DTLCDR doi.org
Target-based multimodal framework for preclinical cancer drug response prediction and transfer to clinical response, with explicit unseen-drug generalization.
-
BABEL github.com
Cross-modality translation model enabling prediction between scRNA-seq and scATAC-seq profiles without requiring paired single-cell measurements.
-
CAPTAIN doi.org
Multimodal foundation model pretrained on co-assayed single-cell RNA and protein for joint representation learning and cross-modal downstream tasks.
-
PerturbRx arxiv.org
Treatment-conditioned representation learning framework that transfers drug-induced latent transitions learned from single-cell perturbation data to patient-level cancer treatment-response prediction.
Computational Biology › Machine Learning Tasks and Models > Drug Discovery > Drug Perturbation: “Cross-dataset model for globally unseen-compound response prediction using a shared gene representation, discrete diffusion models, and matched drug-contrast supervision.”