bioRxiv: EMBER gene foundation model predicts single and combined perturbation effects

[bioRxiv] Ho, Xing and Ma present EMBER, a gene-centric foundation model that learns context-dependent functional representations of genes, according to a bioRxiv preprint. EMBER combines interaction-guided contrastive learning with masked expression reconstruction during pretraining on a single-cell corpus curated for diversity and balanced sampling across cell types and experimental batches. The model decouples gene representation learning from task-specific prediction: the pretrained encoder remains frozen while lightweight probes combine contextualized gene embeddings to predict single-gene perturbation responses, digenic interactions and multi-target drug responses. The authors said EMBER improved cross-context perturbation-response prediction and genetic-interaction ranking relative to evaluated baselines, and prioritized SCFD1, a mediator of autophagosome-lysosome fusion, as a candidate dependency during mTOR inhibition. The findings are from a preprint that has not been peer-reviewed.