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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SNP@Evolution: a hierarchical database of positive selection on the human genome.
PMID 19732458 · PMC2755008 · BMC evolutionary biology · 2009 · 7 claims · 6 setups
SNP@Evolution is a hierarchical database integrating HET, FST, and iHS from HapMap Phase II and III to identify genome-wide positive selection signals
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Gene-centric characteristics of genome-wide association studies.
PMID 18060058 · PMC2092383 · PloS one · 2007 · 8 claims · 5 setups
High-density SNP chips using either direct or indirect selection approaches provide very high coverage in genic regions and capture most known common disease variants under the HapMap framework.
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Coverage and characteristics of the Affymetrix GeneChip Human Mapping 100K SNP set.
PMID 16680197 · PMC1456318 · PLoS genetics · 2006 · 7 claims · 7 setups
SNPs in the Affymetrix 100K set are undersampled from coding regions (both synonymous and nonsynonymous) and oversampled from regions outside genes, relative to HapMap SNPs
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Two novel missense mutations in the myostatin gene identified in Japanese patients with Duchenne muscular dystrophy.
PMID 17428346 · PMC1855920 · BMC medical genetics · 2007 · 7 claims · 5 setups
Two novel missense mutations in the myostatin gene (p.95D>H and p.156L>I) were identified in Japanese DMD patients
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Integrative microRNA and proteomic approaches identify novel osteoarthritis genes and their collaborative metabolic and inflammatory networks.
PMID 19011694 · PMC2582945 · PloS one · 2008 · 8 claims · 8 setups
A 16-microRNA signature (9 up, 7 down) distinguishes osteoarthritic from normal cartilage.
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JIGSAW, GeneZilla, and GlimmerHMM: puzzling out the features of human genes in the ENCODE regions.
PMID 16925843 · PMC1810558 · Genome biology · 2006 · 8 claims · 4 setups
Adding model states for specific biological features (signal peptides, CpG islands, etc.) to non-comparative GHMM gene finders did little or nothing to enhance predictive accuracy, sometimes reducing it.