Experiments
Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).
-
Full-text index only
sCellST predicts single-cell gene expression from H& E images.
PMID 41513659 · PMC12858858 · Nature communications · 2026 · 7 claims · 6 setups
sCellST is a weakly supervised (Multiple Instance Learning) deep learning framework that predicts single-cell gene expression from H&E images alone, trained using paired spatial transcriptomics (Visium) and H&E slides
-
Full-text index only
Reconstructing single-cell resolution from spatial transcriptomics with CellRefiner.
PMID 41760664 · PMC13066420 · Nature communications · 2026 · 8 claims · 8 setups
CellRefiner is a physical/particle-based model (subcellular element method) that integrates scRNA-seq and spatial transcriptomics data to reconstruct single-cell resolution spatial data
-
Full-text index only
A multi-omic single-cell landscape of perinatal mouse skin maps lineage specification and reveals shared dynamics in human fetal skin.
PMID 41998142 · PMC13144478 · Experimental & molecular medicine · 2026 · 7 claims · 8 setups
Integrated scATAC/scRNA multi-omics analysis of developing mouse skin identifies gene network axes underlying skin lineage specification
-
Full-text index only
PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns.
PMID 41673899 · PMC12998178 · Genome biology · 2026 · 7 claims · 8 setups
PreTSA dramatically reduces computational time and memory versus GAM (Monocle, TSCAN) and PseudotimeDE for identifying temporally variable genes (TVGs) while producing highly similar results