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).

• 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

• SNAP predicts effect of mutations on protein function.

  PMID 18757876 · PMC2562009 · Bioinformatics (Oxford, England) · 2008 · 8 claims · 3 setups

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  SNAP is a publicly available web-server implementation predicting functional effects (neutral/non-neutral) of single amino acid substitutions.

  mutant insulin neural alanine mutation

• Using structural bioinformatics to investigate the impact of non synonymous SNPs and disease mutations: scope and limitations.

  PMID 19758473 · PMC2745591 · BMC bioinformatics · 2009 · 8 claims · 8 setups

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  None of 39 tested structural properties can be used as a sole classification criterion to separate neutral SNPs from disease mutations.

  ensembl swissprot same structural foldx side

• Prediction by graph theoretic measures of structural effects in proteins arising from non-synonymous single nucleotide polymorphisms.

  PMID 18654622 · PMC2447880 · PLoS computational biology · 2008 · 8 claims · 5 setups

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  Bongo identifies mutations causing local and global structural effects with a remarkably low false positive rate

  p53 1bpi mutations disease-associated graph correlation structural

• 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