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).
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GDSim: accurate simulation for single-cell transcriptomes based on the guided diffusion model.
PMID 41978379 · PMC13076945 · Briefings in bioinformatics · 2026 · 8 claims · 4 setups
GDSim, a label-guided diffusion-based deep generative network, can simulate scRNA-seq data that closely reflects the true distribution of original data
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Evaluating deconvolution methods using real bulk RNA-expression data for robust prognostic insights across cancer types.
PMID 41566530 · PMC12906006 · Genome biology · 2026 · 7 claims · 6 setups
Pseudobulk and real bulk RNA-seq deconvolution performance differ significantly, and method ranking consistency is lower between pseudobulk and real bulk than within either data type alone
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Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data.
PMID 41825449 · PMC13030991 · Cell reports methods · 2026 · 7 claims · 3 setups
NCLUSION matches the performance of state-of-the-art single-cell clustering techniques with significantly reduced runtime
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Benchmarking tools for deciphering cellular crosstalk in spatially-resolved transcriptomics.
PMID 41952215 · PMC13174004 · Genome biology · 2026 · 8 claims · 5 setups
No prior systematic, quantitative benchmark exists for CCI inference methods specifically developed for spatial transcriptomics across multiple platforms
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OTMODE: an optimal transport theory-based framework for identifying differential features in single-cell multi-omics data.
PMID 41335419 · PMC12766913 · Bioinformatics (Oxford, England) · 2026 · 8 claims · 8 setups
OTMODE, using an unbalanced Sinkhorn algorithm and Wald test, improves differential feature identification in single-cell multi-omics data
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A multi-modal diffusion model with dual-cross-attention for multi-omics data generation and translation.
PMID 41980989 · PMC13253844 · Nature communications · 2026 · 8 claims · 7 setups
scDiffusion-X is a multi-modal latent denoising diffusion probabilistic model for single-cell multi-omics data generation, translation, and interpretation.