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).

• Cell type-specific eQTL analysis of COVID-19 based on single-cell transcriptomic data.

  PMID 41064594 · PMC12501775 · NAR genomics and bioinformatics · 2025 · 8 claims · 8 setups

  Has reproduction · 51

  Single-cell eQTL analysis across eight immune cell types identified 2593 genes whose expression is significantly associated with common genetic polymorphisms, with most genes showing cell type-specific effects

  pbmcs eight pbmc monocytes scrna-seq genetic cis-eqtl

• Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal.

  PMID 41746282 · PMC12998610 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 5 setups

  Full-text index only

  dominoSignal extends the Domino algorithm to enable statistical testing of differential cell-cell signaling between experimental conditions.

  single-cell simulated pdac per-sample single-cell simulation cell-cell

• Anti-CSF-1R therapy with combined immuno-chemotherapy coordinate an adaptive immune response to eliminate macrophage enriched triple negative breast cancers.

  PMID 41484081 · PMC12858953 · Nature communications · 2026 · 8 claims · 8 setups

  Full-text index only

  Combined low-dose CTX + anti-CSF-1R (SNDX-ms6352) is highly effective against aggressive metastatic Trp53-null TNBC models with high macrophage infiltration, producing complete tumor regression in claudin-low models.

  trp53-null complete t12 cell-deficient imaging survival tumor

• FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis.

  PMID 41839892 · PMC13201544 · Nature communications · 2026 · 8 claims · 6 setups

  Full-text index only

  FineST, a bimodal contrastive learning model integrating histology (Virchow2 ViT features) and spatial gene expression, enables nuclei-resolved high-resolution RNA imputation.

  colorectal crc breast he-stained spatial type ccc