EpiFoundation
Foundation model for scATAC-seq using peak-to-gene aligned pretraining for cell representation, annotation, batch correction, and gene-expression prediction.
- from
- Computational Biology
- added
- 2026-10-10
- likes
- 0
similar
-
EpiAgent github.com
scATAC-seq foundation model pretrained on ~5M cells and >35B tokens for representation learning, annotation, imputation, perturbation prediction, and in-silico cCRE knockout.
-
Atacformer doi.org
Transformer foundation model for scATAC-seq that learns embeddings of cis-regulatory elements for clustering, annotation, and reference mapping.
-
ChromFound github.com
Genome-aware scATAC-seq foundation model pretrained on 1.97M cells across tissues and disease contexts for zero-shot cell representations, annotation, and cross-omics prediction.
-
SCARF doi.org
Single-cell RNA+ATAC foundation model pretrained on >2.7M cells for multimodal representation, matching, cross-omics translation, and few-shot annotation.
-
scFoundation github.com
Large-scale foundation model for single-cell gene expression, enabling multiple downstream tasks.
-
DeepSpot github.com
Deep learning model predicting spatial transcriptomics from H&E images at spot and single-cell resolution.
Computational Biology › Machine Learning Tasks and Models > Foundation Models > Single-Cell Epigenomics Foundation Models: “Foundation model for scATAC-seq using peak-to-gene aligned pretraining for cell representation, annotation, batch correction, and gene-expression prediction.”