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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iAODE for benchmarking and continuum modeling of single-cell chromatin accessibility.
PMID 41775921 · PMC13066597 · Communications biology · 2026 · 8 claims · 5 setups
iAODE combines a ZINB-likelihood VAE, a latent Neural ODE, low-weight KL regularization, and an interpretable reconstruction (irecon) bottleneck to learn generative, temporally continuous latent spaces for scATAC-seq.
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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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Has reproduction · 73
treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses.
PMID 34001188 · PMC8127214 · Genome biology · 2021 · 7 claims · 6 setups
treeclimbR proposes multiple candidate resolutions on a tree and selects the optimal one in a data-driven manner using three criteria (FDR-controlling range of t, number of rejected leaves, fewest internal nodes)
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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.
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Protocol to perform cell-type-specific transcriptome-wide association study using scPrediXcan framework.
PMID 41689808 · PMC12925207 · STAR protocols · 2026 · 6 claims · 6 setups
scPrediXcan enables cell-type-specific transcriptome-wide association studies (TWAS) by integrating deep learning-based prediction of gene expression from DNA sequence and epigenetic features.