scGen

Use when working with chemCPA for single-cell perturbation response modeling, especially prediction of cellular responses to unseen drugs, transfer learning from bulk to single-cell perturbation data,

1 shared topic • 3 shared operations

NicheNet — R-based computational framework for studying intercellular communication from single-cell transcriptomics. Predicts which ligands expressed by sender cell types regulate target gene express

1 shared topic • 3 shared operations

AntiFold — antibody-specific inverse folding model built on ESM-IF1, fine-tuned on antibody structures from SAbDab and OAS databases. Predicts residue log-likelihoods for antibody variable domains (IM

2 shared topics • 1 shared operation

GLUE (Graph-Linked Unified Embedding) — deep learning framework for integrating unpaired single-cell multi-omics data (scRNA-seq, scATAC-seq, snmC-seq). Uses a guidance graph of prior regulatory inter

2 shared topics • 1 shared operation

sciPENN — neural network model for single-cell protein expression imputation and multi-omics integration. Transfers protein predictions from CITE-seq (paired RNA+protein) training data to unpaired RNA

2 shared topics • 1 shared operation