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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Has reproduction · 71
Spatial organization shapes the turnover of a bacterial transcriptome.
PMID 27198188 · PMC4874777 · eLife · 2016 · 8 claims · 5 setups
The E. coli transcriptome is spatially organized: mRNAs encoding inner-membrane proteins are enriched at the membrane, while mRNAs encoding cytoplasmic, periplasmic, and outer-membrane proteins are distributed throughout the cytoplasm.
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Decoding the Mechanisms of Hepatocellular Carcinoma Cancer Stem Cells and Identifying Potential Therapeutic Strategies Based on Single-cell Omics.
PMID 41771574 · PMC12951371 · Cancer genomics & proteomics · 2026 · 7 claims · 8 setups
Malignant cells from HCC tumors resolve into six transcriptionally distinct subpopulations, including a progenitor-like CSC subset expressing EPCAM, SOX9, and SOX4
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SGCRNA: spectral clustering-guided co-expression network analysis without scale-free constraints for multi-omic data.
PMID 41615289 · PMC12856952 · Briefings in bioinformatics · 2026 · 8 claims · 8 setups
WGCNA's reliance on a scale-free topology assumption is problematic because real co-expression networks do not consistently exhibit scale-free properties
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scArchon: a scalable benchmarking framework for assessing single-cell perturbation models.
PMID 42121287 · PMC13162514 · Genome biology · 2026 · 8 claims · 8 setups
scArchon is a reproducible, modular, Snakemake-based benchmarking platform that evaluates perturbation response prediction tools in a standardized, containerized, extensible manner.
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Has reproduction · 85
Optimisation of the core subset for the APY approximation of genomic relationships.
PMID 36418945 · PMC9682752 · Genetics, selection, evolution : GSE · 2022 · 7 claims · 3 setups
APY approximates the full genomic relationship matrix by splitting genotyped animals into a core subset (fully dependent, direct inverse) and a non-core subset (conditionally independent given core), reducing inversion cost.
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Statistical challenges in preprocessing in microarray experiments in cancer.
PMID 18829474 · PMC3529914 · Clinical cancer research : an official journal of the American Association for Cancer Research · 2008 · 8 claims · 7 setups
Choice of pre-processing method materially changes which features are found significantly associated with survival in the Beer et al. lung cancer microarray dataset