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 · 85
A mechanistic model captures the emergence and implications of non-genetic heterogeneity and reversible drug resistance in ER+ breast cancer cells.
PMID 34316714 · PMC8271219 · NAR cancer · 2021 · 7 claims · 8 setups
EMT and tamoxifen-resistance (TamR) regulatory axes can drive one another, enabling non-genetic heterogeneity via six co-existing phenotypes (ES, ER, HS, HR, MS, MR)
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BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments.
PMID 16845052 · PMC1538844 · Nucleic acids research · 2006 · 8 claims · 8 setups
Babelomics is presented as an updated, complete suite of web tools for functional analysis of genome-scale experiments with new and improved modules
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Identification and analysis of co-occurrence networks with NetCutter.
PMID 18781200 · PMC2526157 · PloS one · 2008 · 8 claims · 4 setups
Random sampling from a complete permutation set of the bipartite graph permits co-occurrence analysis with optimal stringency, and the edge-swapping (ES) model closely approximates this and is the preferred null-model among six tested.
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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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Genome-wide analysis of human disease alleles reveals that their locations are correlated in paralogous proteins.
PMID 18989397 · PMC2565504 · PLoS computational biology · 2008 · 7 claims · 5 setups
The locations of sequence variants are correlated between paralogous human proteins more than expected by chance.
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Disease-aging network reveals significant roles of aging genes in connecting genetic diseases.
PMID 19779549 · PMC2739292 · PLoS computational biology · 2009 · 8 claims · 8 setups
Human disease genes are much closer to aging genes in the PPI network than expected by chance