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 · 87
Ultra-deep sequencing data from a liquid biopsy proficiency study demonstrating analytic validity.
PMID 35418127 · PMC9008010 · Scientific data · 2022 · 6 claims · 5 setups
This dataset is the most comprehensive public-facing dataset of ultra-deep ctDNA sequencing data generated to date
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Proteomic solutions for analytical challenges associated with alcohol research.
PMID 23584870 · PMC3860482 · Alcohol research & health : the journal of the National Institute on Alcohol Abuse and Alcoholism · 2008 · 7 claims · 4 setups
Protein-level meta-analyses analogous to the transcriptome meta-analysis by Mulligan et al. (2006) are not yet possible because proteins lack a uniform sample preparation/analysis method and span up to 8 orders of magnitude in abundance.
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Has reproduction · 99
Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing.
PMID 34103501 · PMC8187371 · Nature communications · 2021 · 7 claims · 4 setups
Nanopore methylation detection tools exhibit a tradeoff between false positives and false negatives and high dispersion relative to expected per-site methylation frequencies.
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Has reproduction · 50
Performance of methods for SARS-CoV-2 variant detection and abundance estimation within mixed population samples.
PMID 36721781 · PMC9884472 · PeerJ · 2023 · 8 claims · 4 setups
Kallisto was the most accurate VCE on simulated data, having the lowest RRMSE, followed by Freyja
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A rational approach for discovering and validating cancer markers in very small samples using mass spectrometry and ELISA microarrays.
PMID 15502246 · PMC3839270 · Disease markers · 2004 · 8 claims · 4 setups
A two-stage strategy combining MS proteomics for discovery and ELISA microarrays for validation can identify and characterize cancer markers in very small samples