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).

• Deconvolving cell-type-specific gene expression profiles from bulk RNA-seq samples.

  PMID 41886524 · PMC13038110 · PLoS computational biology · 2026 · 8 claims · 6 setups

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  BLUE, a U-Net-based deep learning model with dual branches (U-Net for GEPs, MLP for proportions), accurately predicts cell-type proportions and cell-type-specific gene expression profiles from bulk RNA-seq.

  pbmc pancreatic aml scrna-seq-derived real scrna-seq

• PreTSA: computationally efficient modeling of temporal and spatial gene expression patterns.

  PMID 41673899 · PMC12998178 · Genome biology · 2026 · 7 claims · 8 setups

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  PreTSA dramatically reduces computational time and memory versus GAM (Monocle, TSCAN) and PseudotimeDE for identifying temporally variable genes (TVGs) while producing highly similar results

  simulated null pbmc pancreas pseudotime tvg false-positive

• Benchmarking tools for deciphering cellular crosstalk in spatially-resolved transcriptomics.

  PMID 41952215 · PMC13174004 · Genome biology · 2026 · 8 claims · 5 setups

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  No prior systematic, quantitative benchmark exists for CCI inference methods specifically developed for spatial transcriptomics across multiple platforms

  synthetic real simulated simulation spot-purity real-data