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).

• Epidemiology of doublet/multiplet mutations in lung cancers: evidence that a subset arises by chronocoordinate events.

  PMID 19005564 · PMC2579325 · PloS one · 2008 · 8 claims · 7 setups

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  Doublet mutations are significantly more frequent in EGFR (6.0%) and TP53 (2.3%) in human lung cancer than spontaneous doublets in mouse lacI (0.7%), about 8-fold and 3-fold higher respectively.

  egfr tp53 laci lung literature comparative statistical

• Sequence and structure signatures of cancer mutation hotspots in protein kinases.

  PMID 19834613 · PMC2759519 · PloS one · 2009 · 8 claims · 6 setups

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  Developed CKMD (Composite Kinase Mutation Database), an integrated bioinformatics resource mapping genetic variation in protein kinase genes to sequence, structural, and functional data

  kinase common egfr autoinhibited database-driven structure-informed evolutionary

• Oncogene mutations, copy number gains and mutant allele specific imbalance (MASI) frequently occur together in tumor cells.

  PMID 19826477 · PMC2757721 · PloS one · 2009 · 8 claims · 8 setups

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  Homozygous mutations of oncogenes are frequent (20%) across 833 cancer cell lines of 12 tumor types in the Sanger database

  tumors cancer tumor lung direct database quantitative

• A mouse plasma peptide atlas as a resource for disease proteomics.

  PMID 18522751 · PMC2481425 · Genome biology · 2008 · 8 claims · 6 setups

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  A publicly available, high-quality mouse plasma peptide/protein repository (mouse PeptideAtlas) was built from 568 LC-MS/MS runs on four reference plasma pools.

  plasma peptides fully tissues lc-ms anion database

• Cancer-specific high-throughput annotation of somatic mutations: computational prediction of driver missense mutations.

  PMID 19654296 · PMC2763410 · Cancer research · 2009 · 7 claims · 7 setups

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  CHASM, a Random Forest-based computational method, was developed to identify and prioritize missense mutations likely to be functional drivers of tumor cell proliferation.

  missense same synthetic tp53 random support principal