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).

• sCellST predicts single-cell gene expression from H& E images.

  PMID 41513659 · PMC12858858 · Nature communications · 2026 · 7 claims · 6 setups

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  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

  ovarian kidney prostate breast simulation spot-level nucleus

• scSNViz: visualization and analysis of cell-specific expressed SNVs.

  PMID 41533688 · PMC12866635 · Bioinformatics (Oxford, England) · 2026 · 7 claims · 7 setups

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  scSNViz is an R package for exploration, quantification, and visualization of expressed SNVs from cell-barcoded scRNA-seq data, supporting VAF estimation, SNV clustering, and 2D/3D visualization.

  prostate non-small cholangiocarcinoma neuroblastoma scrna-seq cell-level single-cell

• Cancer-wide in silico analyses using differentially expressed genes demonstrate the functions and clinical relevance of JAG, DLL, and NOTCH.

  PMID 39074091 · PMC11285958 · PloS one · 2024 · 7 claims · 8 setups

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  JAG, DLL, and NOTCH family gene/protein expression varies diversely across 15 cancer types relative to normal tissue, sometimes discordant between mRNA and protein levels.

  tumor degs cancer jag bulk proteomics gene