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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Protocol for quantifying interaction patterns among genomic alterations in cancer.
PMID 41686643 · PMC12915222 · STAR protocols · 2026 · 6 claims · 5 setups
Background-aware permutation strategies that constrain permutation per gene and per sample enable robust, scalable inference of condition-specific (context-aware) genetic interactions across cancer cohorts
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Recurring mutations found by sequencing an acute myeloid leukemia genome.
PMID 19657110 · PMC3201812 · The New England journal of medicine · 2009 · 8 claims · 8 setups
Deep paired tumor/normal whole-genome sequencing of a cytogenetically normal AML-M1 genome identified 12 somatic coding (tier 1) mutations and 52 somatic tier 2 (conserved/regulatory) mutations.
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Has reproduction · 84
Single-cell protein activity analysis reveals aberrant myogenesis and IGF2-PI3K pathway dependencies in MYOD1-mutant rhabdomyosarcoma.
PMID 41758938 · PMC12947870 · Science advances · 2026 · 8 claims · 8 setups
MYOD1 L122R-mutant SRMS tumors contain three coexisting, conserved cell states (progenitor, transition, differentiated) reflecting aberrant myogenic differentiation
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Human synthetic lethal inference as potential anti-cancer target gene detection.
PMID 20015360 · PMC2804737 · BMC systems biology · 2009 · 7 claims · 8 setups
Targeting the synthetic lethal partner of a gene mutated in cancer selectively damages tumor cells while sparing healthy cells, offering a rationale for anti-cancer drug design
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Extraction of human kinase mutations from literature, databases and genotyping studies.
PMID 19758464 · PMC2745582 · BMC bioinformatics · 2009 · 7 claims · 6 setups
A literature mining pipeline combining MutationFinder, false-positive filtering, and SVM-based classification can extract and disambiguate single-point mutation mentions from abstracts and full text