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).

• DiSCO: deconvoluting spatial transcriptomics via combinatorial optimization with a foundational diffusion model.

  PMID 42101928 · PMC13155122 · Briefings in bioinformatics · 2026 · 7 claims · 2 setups

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  Deconvolution of spatial transcriptomics data can be formulated as a combinatorial optimization (CO) problem of assigning single cells to spatial spots so that aggregated single-cell profiles best approximate observed spot expression

  sccube-simulated real simulation-based spatial

• Differential expression analysis in single-cell and spatial RNA-seq without model assumptions.

  PMID 41980775 · PMC13198004 · Cell reports methods · 2026 · 7 claims · 4 setups

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  Common DGE analysis methods (Wilcoxon test, unweighted t-test, pseudo-bulk aggregation, SCTransform-style parametrization) rely on unnecessary simplifications and assumptions that are inconsistent with experimental data and cause false findings

  e18 simulated scrna-seq sprna-seq scrna-seq simulation count

• scSurv: a deep generative model for single-cell survival analysis.

  PMID 41429574 · PMC12797213 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 6 setups

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  scSurv combines a Cox proportional hazards model with a deep generative model (VAE) of single-cell transcriptomes to estimate individual cellular contributions to clinical outcomes

  simulated tcga melanoma renal scrna-seq bulk single-cell