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

• GeneExt: a gene model extension tool for enhanced single-cell RNA-seq analysis.

  PMID 41769841 · PMC12970594 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups

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  Incomplete/inaccurate gene annotations, especially missing or truncated 3' UTRs, cause reads to map to non-genic regions and genes to be under-quantified or missing from scRNA-seq expression matrices in non-model species

  genomes whole-organism xenia octopus peak scrna-seq