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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BRCA1 and BRCA2 mutation predictions using the BOADICEA and BRCAPRO models and penetrance estimation in high-risk French-Canadian families.
PMID 16417652 · PMC1413985 · Breast cancer research : BCR · 2006 · 8 claims · 7 setups
BOADICEA predicts accurately the number of BRCA1 and BRCA2 mutations across family groups and discriminates well between carriers and noncarriers
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Evaluation of models to predict BRCA germline mutations.
PMID 17016486 · PMC2360540 · British journal of cancer · 2006 · 7 claims · 7 setups
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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Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants?
PMID 18036263 · PMC2246181 · Breast cancer research : BCR · 2007 · 8 claims · 8 setups
Revised multifactorial likelihood analysis incorporating ER, CK5/6, and CK14 tumor immunohistochemistry improves classification of BRCA1 unclassified variants
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Prediction and assessment of splicing alterations: implications for clinical testing.
PMID 18951448 · PMC2832470 · Human mutation · 2008 · 8 claims · 5 setups
Bioinformatic prediction alone is insufficient; in vitro analysis is needed to confirm or establish splicing aberrations for clinical variant classification
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Evaluation of BRCA1 and BRCA2 mutations and risk-prediction models in a typical Asian country (Malaysia) with a relatively low incidence of breast cancer.
PMID 18627636 · PMC2575532 · Breast cancer research : BCR · 2008 · 8 claims · 5 setups
27 deleterious BRCA1/BRCA2 mutations were detected in 28 breast cancer patients (14 in BRCA1, 13 in BRCA2) among 187 tested
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Iterative class discovery and feature selection using Minimal Spanning Trees.
PMID 15355552 · PMC520744 · BMC bioinformatics · 2004 · 7 claims · 5 setups
Iterating between MST-based clustering and t-statistic feature selection removes noise genes step-wise while sharpening the sample clustering
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In silico analysis of missense substitutions using sequence-alignment based methods.
PMID 18951440 · PMC3431198 · Human mutation · 2008 · 8 claims · 7 setups
Carefully validated PMSA-based computational algorithms can achieve predictive values of ~75-95% for classifying missense substitutions as pathogenic or neutral.