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

  Full-text index only

  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

• An NMF-Based Methodology for Selecting Biomarkers in the Landscape of Genes of Heterogeneous Cancer-Associated Fibroblast Populations.

  PMID 32425511 · PMC7218276 · Bioinformatics and biology insights · 2020 · 8 claims · 6 setups

  Has reproduction · 84

  An integrated methodology combining nonnegative matrix factorization (NMF), the WebGestalt functional enrichment tool, and an ad hoc gene extraction procedure automatically identifies informative gene subsets from microarray data matrices that differ in number of genes (rows) and patients (columns)

  caf bone extracted microarray functional