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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Spectrum and characterisation of BRCA1 and BRCA2 deleterious mutations in high-risk Czech patients with breast and/or ovarian cancer.
PMID 18489799 · PMC2413254 · BMC cancer · 2008 · 8 claims · 6 setups
Pathogenic BRCA1/BRCA2 mutations were identified in 294 of 1,010 (29.1%) unrelated high-risk Czech probands
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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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Has reproduction · 85
Predicting the pathogenicity of missense variants using features derived from AlphaFold2.
PMID 37084271 · PMC10203375 · Bioinformatics (Oxford, England) · 2023 · 6 claims · 8 setups
AlphaFold2-derived structural features (solvent accessibility, amino acid network features, physicochemical environment, pLDDT) can be used to train a random forest classifier (AlphScore) that distinguishes proxy-benign from proxy-pathogenic missense variants.
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MicroRNA profiling of BRCA1/2 mutation-carrying and non-mutation-carrying high-grade serous carcinomas of ovary.
PMID 19798417 · PMC2749450 · PloS one · 2009 · 7 claims · 7 setups
High grade serous carcinomas with and without BRCA1/2 abnormalities show very similar miRNA expression profiles, with no clear clustering separation by BRCA1/2 status
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Analysis of a set of missense, frameshift, and in-frame deletion variants of BRCA1.
PMID 18992264 · PMC2682550 · Mutation research · 2009 · 8 claims · 8 setups
A combined functional assay, bioinformatics prediction, and structural modeling approach can classify BRCA1 variants of uncertain significance
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ATM variants and cancer risk in breast cancer patients from Southern Finland.
PMID 16914028 · PMC1592307 · BMC cancer · 2006 · 8 claims · 6 setups
Neither 5557G>A nor ivs38-8T>C, nor any haplotype containing them, was significantly associated with breast cancer risk in any patient group
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Has reproduction · 51
Evaluation of the Available Variant Calling Tools for Oxford Nanopore Sequencing in Breast Cancer.
PMID 36140751 · PMC9498802 · Genes · 2022 · 7 claims · 6 setups
Clair3 and Human-SNP-wf (which incorporates Clair3) achieved the highest performance among the six variant callers tested.
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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.
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An integrated database-pipeline system for studying single nucleotide polymorphisms and diseases.
PMID 19091018 · PMC2638159 · BMC bioinformatics · 2008 · 6 claims · 5 setups
Existing SNP/disease databases are fragmented; no combined resource widely supports gene-, SNP-, and disease-related information together