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).

• Evaluation of models to predict BRCA germline mutations.

  PMID 17016486 · PMC2360540 · British journal of cancer · 2006 · 7 claims · 7 setups

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  Four commonly used BRCA risk prediction models (BRCAPRO, Manchester, Penn, Myriad-Frank) have only modest ability to rule in or rule out BRCA1/2 germline mutation carrier status at a 10% probability threshold.

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• Application of two machine learning algorithms to genetic association studies in the presence of covariates.

  PMID 19014573 · PMC2620353 · BMC genetics · 2008 · 8 claims · 3 setups

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  The relative performance of RF and MARS for detecting genotype-trait associations depends on both the strategy used to handle covariates and the true underlying model of association (e.g., confounding vs. mediation vs. interaction).

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• Filtering high-throughput protein-protein interaction data using a combination of genomic features.

  PMID 15833142 · PMC1127019 · BMC bioinformatics · 2005 · 8 claims · 8 setups

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  A combination of three genomic features (interacting Pfam domains, GO annotations, sequence homology) using naive Bayesian networks predicts true protein-protein interactions with high sensitivity and good specificity.

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• Systems biology in human health and disease.

  PMID 17893698 · PMC2013921 · Molecular systems biology · 2007 · 8 claims · 5 setups

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  High-throughput quantitative proteomics of signaling networks (e.g., HER2 overexpression) can be correlated with biological responses like proliferation and migration to better understand pathways deregulated in cancer.

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• From single cells to whole organisms.

  PMID 16420683 · PMC1414103 · Genome biology · 2005 · 8 claims · 8 setups

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  The genetic-interaction map in S. cerevisiae is roughly four times as complex as the protein-protein interaction map, and genetic interactions do not overlap with physical interactions but instead predict functional neighborhoods

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