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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A metadata approach for clinical data management in translational genomics studies in breast cancer.
PMID 19948017 · PMC3225860 · BMC medical genomics · 2009 · 8 claims · 5 setups
A metadata/CDE-based approach using CancerGrid's semantic web tools enables automatic integration of heterogeneous clinical datasets without loss of original detail
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High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer.
PMID 17925008 · PMC2246289 · Genome biology · 2007 · 7 claims · 8 setups
A novel subtype of high-grade ER-negative breast cancer exists, characterized by a low genomic instability index (GII)
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The diagnosis and management of pre-invasive breast disease: promise of new technologies in understanding pre-invasive breast lesions.
PMID 14580250 · PMC314415 · Breast cancer research : BCR · 2003 · 8 claims · 8 setups
ADH and ductal carcinoma in situ (DCIS) are precursor lesions molecularly similar to adjacent invasive breast cancer
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Divide and conquer: progress in the molecular stratification of cancer.
PMID 19718393 · PMC2730607 · Yonsei medical journal · 2009 · 8 claims · 8 setups
Cancers exhibit significant clinical, histopathologic, and molecular heterogeneity between individual patients
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Re-evaluating early breast neoplasia.
PMID 18279539 · PMC2374963 · Breast cancer research : BCR · 2008 · 8 claims · 7 setups
The classic single linear model of breast cancer progression requires revision based on high-throughput molecular genetic and gene expression data.
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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.