Associated Papers
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-s002.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
Consolidated BRCA1/2 Variant Interpretation by MH BRCA Correlates with Predicted PARP Inhibitor Efficacy Association by MH Guide.
Hirotsu Y et al.
International Journal of Molecular Sciences, 2020
32486089 (PubMed )
Supplement: ijms-21-03895-s001.zip › Supplemental_Table_2.xlsx › ARUP
Analysis of the pathogenic variants of BRCA1 and BRCA2 using next-generation sequencing in women with familial breast cancer: a case-control study.
Zayas-Villanueva OA et al.
Bmc Cancer, 2019
31331294 (PubMed )
Supplement: 12885_2019_5950_MOESM1_ESM.xlsx › Healthy
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
Population and breast cancer patients' analysis reveals the diversity of genomic variation of the BRCA genes in the Mexican population.
Fernández-Lopez JC et al.
Human Genomics, 2019
30630528 (PubMed )
Supplement: 40246_2018_188_MOESM3_ESM.xlsx › Hoja1
Somatic mutations in early onset luminal breast cancer.
Encinas G et al.
Oncotarget, 2018
29854292 (PubMed )
Supplement: oncotarget-09-22460-s002.xlsx › Supplementary_Table3
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
Germline mutations in BRCA1 and BRCA2 in epithelial ovarian cancer patients in Brazil.
Maistro S et al.
Bmc Cancer, 2016
27914478 (PubMed )
Supplement: 12885_2016_2966_MOESM1_ESM.zip › Additional_tables.xlsx › Table_S3
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_9._Validated_Variantsv2.xlsx › Supplementary_Table_9
Intronic alterations in BRCA1 and BRCA2: effect on mRNA splicing fidelity and expression.
Chen X et al.
Human Mutation, 2006
Select a paper to view details