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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Metabolic syndrome: from epidemiology to systems biology.
PMID 18852695 · PMC2829312 · Nature reviews. Genetics · 2008 · 8 claims · 8 setups
MetSyn component traits (obesity, insulin resistance, dyslipidaemia, hypertension) exhibit causal interactions and common etiologies rather than being independent conditions
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Genome-wide prediction of functional gene-gene interactions inferred from patterns of genetic differentiation in mice and men.
PMID 18270580 · PMC2217631 · PloS one · 2008 · 8 claims · 6 setups
Pairs of unlinked SNPs showing excess genetic differentiation (LD in mouse RILs, Fst in human populations) beyond what simulations/coalescent models predict by chance represent candidate functionally interacting (epistatic) gene pairs.
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Meta-analysis of inter-species liver co-expression networks elucidates traits associated with common human diseases.
PMID 20019805 · PMC2787626 · PLoS computational biology · 2009 · 8 claims · 8 setups
A novel semi-parametric meta-analysis method (based on a gene-centric Glass's d effect size) outperforms existing parametric and non-parametric meta-analysis methods at identifying functionally coherent gene pairs across species.
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Adaptations to climate in candidate genes for common metabolic disorders.
PMID 18282109 · PMC2242814 · PLoS genetics · 2008 · 8 claims · 7 setups
A network-based bioinformatics approach (Molecular Triangulation) was used to select 82 candidate genes belonging to the core subnetwork of metabolic syndrome phenotypes.
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Systems genetics of alcoholism.
PMID 23584748 · PMC3860445 · Alcohol research & health : the journal of the National Institute on Alcohol Abuse and Alcoholism · 2008 · 8 claims · 8 setups
Alcoholism is a multifactorial disease driven by interacting genetic, social, and environmental factors, with genetics accounting for 50-60% of risk.
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Policy implications of genetic information on regulation under the Clean Air Act: the case of particulate matter and asthmatics.
PMID 16507451 · PMC1392222 · Environmental health perspectives · 2006 · 8 claims · 4 setups
The Clean Air Act mandates protection of sensitive subpopulations, including asthmatics, from air pollution health effects, creating an opening for genetic susceptibility data in regulation.