Associated Papers
Pathogenic variation in human DNA damage repair genes was originated from the evolutionary process of modern humans.
Li J et al.
Genes & Diseases, 2026
41624906 (PubMed )
Supplement: mmc1.xlsx › Sheet1
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
41263939 (PubMed )
Supplement: supplementary_materials_bbaf611_1_.zip › Supplementary_materials_bbaf611 › Supplementary_Table_S8.xlsx › Sheet1
Pathogenic variants in human DNA damage repair genes mostly arose in recent human history.
Zhao B et al.
Bmc Cancer, 2024
38575974 (PubMed )
Supplement: 12885_2024_12160_MOESM6_ESM.xlsx › Sheet1
Pathogenic variants in human DNA damage repair genes mostly arose after the latest human out-of-Africa migration.
He J et al.
Frontiers in Genetics, 2024
38948361 (PubMed )
Supplement: Table6.XLSX › Sheet1
The pathogenic role of the BRCA2 c.7847C>T (p.Ser2616Phe) variant in breast and ovarian cancer predisposition.
Yamazawa K et al.
Cancer Science, 2023
37067535 (PubMed )
Supplement: CAS-114-2993-s001.pdf
SpliceAI-10k calculator for the prediction of pseudoexonization, intron retention, and exon deletion.
Canson DM et al.
Bioinformatics (oxford, England), 2023
37021934 (PubMed )
Supplement: btad179_supplementary_data.zip › SAI10kcalc_supp_tables_final.xlsx › S1.variants
Ethnic-specificity, evolution origin and deleteriousness of Asian BRCA variation revealed by over 7500 BRCA variants derived from Asian population.
Qin Z et al.
International Journal of Cancer, 2023
36385461 (PubMed )
Supplement: IJC-152-1159-s006.xlsx › BRCA2
APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP.
Walker LC et al.
Medrxiv : the Preprint Server for Health Sciences, 2023
36865205 (PubMed )
Supplement: media-10.xlsx › Table_S2
A Comprehensive Evaluation of the Performance of Prediction Algorithms on Clinically Relevant Missense Variants.
Qorri E et al.
International Journal of Molecular Sciences, 2022
35887294 (PubMed )
Supplement: ijms-23-07946-s001.zip › Supplementary_Table_S4.xlsx › BRCA2_Dataset
Understanding and predicting the functional consequences of missense mutations in BRCA1 and BRCA2.
Aljarf R et al.
Scientific Reports, 2022
35729312 (PubMed )
Supplement: 41598_2022_13508_MOESM2_ESM.xlsx › Sheet1
Breast cancer risks associated with missense variants in breast cancer susceptibility genes.
Dorling L et al.
Genome Medicine, 2022
35585550 (PubMed )
Supplement: 13073_2022_1052_MOESM2_ESM.xlsx › Table_S3
Human BRCA pathogenic variants were originated during recent human history.
Li J et al.
Life Science Alliance, 2022
Analysis of single-nucleotide polymorphisms in genes associated with triple-negative breast cancer.
G V et al.
Frontiers in Genetics, 2022
36561320 (PubMed )
Supplement: Table3.xlsx › Sheet1
Prevalence of Germline Pathogenic Variants in Cancer Predisposing Genes in Czech and Belgian Pancreatic Cancer Patients.
Wieme G et al.
Cancers, 2021
34503238 (PubMed )
Supplement: cancers-13-04430-s001.zip › Supl_tables_zip_cancers › Suppl_Table_S4.xlsx › Blad1
Pathogenic nsSNPs that increase the risks of cancers among the Orang Asli and Malays.
Khoruddin NA et al.
Scientific Reports, 2021
34373545 (PubMed )
Supplement: 41598_2021_95618_MOESM1_ESM.xlsx › Training_Dataset
Identification of Germline Mutations in Melanoma Patients with Early Onset, Double Primary Tumors, or Family Cancer History by NGS Analysis of 217 Genes.
Stolarova L et al.
Biomedicines, 2020
Patient specific circulating tumor DNA fingerprints to monitor treatment response across multiple tumors.
Li J et al.
Journal of Translational Medicine, 2020
32738923 (PubMed )
Supplement: 12967_2020_2449_MOESM2_ESM.xlsx › Supplementary_Table_S1
High-throughput functional evaluation of BRCA2 variants of unknown significance.
Ikegami M et al.
Nature Communications, 2020
Classification of variants of uncertain significance in BRCA1 and BRCA2 using personal and family history of cancer from individuals in a large hereditary cancer multigene panel testing cohort.
Li H et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2020
31853058 (PubMed )
Supplement: 41436_2019_729_MOESM3_ESM.xls › Sheet1
Optimizing clinical exome design and parallel gene-testing for recessive genetic conditions in preconception carrier screening: Translational research genomic data from 14,125 exomes.
Capalbo A et al.
Plos Genetics, 2019
31589614 (PubMed )
Supplement: pgen.1008409.s003.xlsx › Secondary_Findings_P_LP_Variant
REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.
Tian Y et al.
Scientific Reports, 2019
31484976 (PubMed )
Supplement: 41598_2019_49224_MOESM2_ESM.xlsx › Sheet1
Germline variation in BRCA1/2 is highly ethnic-specific: Evidence from over 30,000 Chinese hereditary breast and ovarian cancer patients.
Bhaskaran SP et al.
International Journal of Cancer, 2019
30702160 (PubMed )
Supplement: IJC-145-962-s006.xlsx › BRCA2_ethnic_sources_
A plugin for the Ensembl Variant Effect Predictor that uses MaxEntScan to predict variant spliceogenicity.
Shamsani J et al.
Bioinformatics (oxford, England), 2019
30475984 (PubMed )
Supplement: bty960_supplementary_data.zip › bty960-Suppl_data › Supplementary_Table_S1.xlsx › Sheet1
Twenty Years of BRCA1 and BRCA2 Molecular Analysis at MMCI - Current Developments for the Classification of Variants.
Machackova E et al.
Klinicka Onkologie : Casopis Ceske a Slovenske Onkologicke Spolecnosti, 2019
Corrigendum: Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.
Leman R et al.
Nucleic Acids Research, 2018
30321405 (PubMed )
Supplement: gky979_supplemental_files.zip › Corrigendum_supplementary_table.xlsx › AllData
Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico/in vitro studies: an international collaborative effort.
Leman R et al.
Nucleic Acids Research, 2018
29750258 (PubMed )
Supplement: gky372_supplemental_files.zip › SPiCE_table_supp.R2.xlsx › Table_S2
A comprehensive analysis of BRCA2 gene: focus on mechanistic aspects of its functions, spectrum of deleterious mutations, and therapeutic strategies targeting BRCA2-deficient tumors.
Shailani A et al.
Medical Oncology (northwood, London, England), 2018
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
30212499 (PubMed )
Supplement: pone.0203553.s008.xlsx › Variants
Computational Tools for Splicing Defect Prediction in Breast/Ovarian Cancer Genes: How Efficient Are They at Predicting RNA Alterations?
Moles-Fernández A et al.
Frontiers in Genetics, 2018
30233647 (PubMed )
Supplement: Table_1.XLSX › Supplem_Table_6
Identification of a Novel BRCA1 Pathogenic Mutation in Korean Patients Following Reclassification of BRCA1 and BRCA2 Variants According to the ACMG Standards and Guidelines Using Relevant Ethnic Controls.
Park JS et al.
Cancer Research and Treatment, 2017
Male breast cancer in a multi-gene panel testing cohort: insights and unexpected results.
Pritzlaff M et al.
Breast Cancer Research and Treatment, 2017
The prevalence and spectrum of BRCA1 and BRCA2 mutations in Korean population: recent update of the Korean Hereditary Breast Cancer (KOHBRA) study.
Kang E et al.
Breast Cancer Research and Treatment, 2015
MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing.
Mort M et al.
Genome Biology, 2014
24451234 (PubMed )
Supplement: gb-2014-15-1-r19-S1.pdf
Interpretation of mRNA splicing mutations in genetic disease: review of the literature and guidelines for information-theoretical analysis.
Caminsky N et al.
F1000research, 2014
25717368 (PubMed )
Supplement: f1000research-3-6038-s0000.tgz › e0d3facd-5877-477e-9217-8c5aa68746f2_Supplementary-Tables-11112014.zip › Supplementary-Tables-and-Figures-11112014 › Supplementary_Table_10._Splicing_Mutation_Calculator_Source_Datav2.xlsx › Supplementary_Table_10
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