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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Integration of text- and data-mining using ontologies successfully selects disease gene candidates.
PMID 15767279 · PMC1065256 · Nucleic acids research · 2005 · 7 claims · 6 setups
Integrating eVOC anatomical ontology-based text-mining of PubMed abstracts with data-mining of gene expression annotation successfully selects and prioritizes candidate disease genes
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Loss of heterozygosity at 2q37 in sporadic Wilms' tumor: putative role for miR-562.
PMID 19789318 · PMC2756455 · Clinical cancer research : an official journal of the American Association for Cancer Research · 2009 · 8 claims · 8 setups
2q37 harbors a tumor suppressor gene important in Wilms tumor pathogenesis
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A candidate metastasis-associated DNA marker for ductal mammary carcinoma.
PMID 12631399 · PMC154149 · Breast cancer research : BCR · 2003 · 8 claims · 8 setups
RDA comparing normal and metastatic ductal breast carcinoma cell DNA identified 10 unique metastasis-associated DNA sequences (MADS) apparently lost in metastatic cells
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An integrative approach to reveal driver gene fusions from paired-end sequencing data in cancer.
PMID 19881495 · PMC3086882 · Nature biotechnology · 2009 · 8 claims · 8 setups
A 'concept signature' (ConSig) score algorithm ranks genes by association with molecular concepts characteristic of fusion or mutation cancer genes, nominating biologically important fusions from large candidate sets.
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Genomic profiling of CpG methylation and allelic specificity using quantitative high-throughput mass spectrometry: critical evaluation and improvements.
PMID 17855397 · PMC2094090 · Nucleic acids research · 2007 · 8 claims · 5 setups
A new weighted formula that accounts for the number of methylated CpG sites per fragment removes the bias of the original MassCLEAVE™ formula toward higher apparent methylation in fragments with more CpG sites.