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).
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MultiSP deciphers tissue structure and multicellular communication from spatial multi-omics data.
PMID 41650976 · PMC13174227 · Cell genomics · 2026 · 7 claims · 5 setups
MultiSP outperforms existing spatial and single-cell multi-omics integration methods in detecting biologically accurate spatial domains across multiple spatial multi-omics technologies and tissue types
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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
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DANST enables cell-type deconvolution in spatial transcriptomics using deep domain adversarial neural networks.
PMID 41663685 · PMC12996496 · Communications biology · 2026 · 7 claims · 6 setups
DANST, a deconvolution framework using deep domain adversarial neural networks, achieves superior cell-type deconvolution accuracy compared with existing methods on human and mouse benchmark datasets
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Calibrating tissue level PDE models of ligand dynamics using single cell and spatial transcriptomics data.
PMID 41714655 · PMC13039149 · NPJ systems biology and applications · 2026 · 8 claims · 8 setups
scRNA-seq and spatial transcriptomics data provide a rich, underused source of information for calibrating tissue-scale PDE models of ligand dynamics.