Associated Papers
A scalable approach to resolving variants of uncertain significance.
Tejura M et al.
Biorxiv : the Preprint Server for Biology, 2026
Functional assessment of protein variants in structured domains by fluorescence cross-correlation spectroscopy.
Mateu-Regué À et al.
Scientific Reports, 2026
Precision in prediction: tailoring machine learning models for breast cancer missense variants pathogenicity prediction.
Ahmad RM et al.
Briefings in Bioinformatics, 2025
ACMG/AMP interpretation of BRCA1 missense variants: Structure-informed scores add evidence strength granularity to the PP3/BP4 computational evidence.
Ramadane-Morchadi L et al.
American Journal of Human Genetics, 2025
VarMeter2: An enhanced structure-based method for predicting pathogenic missense variants through Mahalanobis distance.
Ohno S et al.
Computational and Structural Biotechnology Journal, 2025
Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification.
Padigepati SR et al.
Human Genetics, 2024
Protein-folding chaperones predict structure-function relationships and cancer risk in BRCA1 mutation carriers.
Gracia B et al.
Cell Reports, 2024
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
Artificial intelligence-based recognition for variant pathogenicity of BRCA1 using AlphaFold2-predicted structures.
Li C et al.
Theranostics, 2023
Evaluation of AlphaFold structure-based protein stability prediction on missense variations in cancer.
Keskin Karakoyun H et al.
Frontiers in Genetics, 2023
Refinement of the assignment to the ACMG/AMP BS3 and PS3 criteria of eight BRCA1 variants of uncertain significance by integrating available functional data with protein interaction assays.
Caleca L et al.
Frontiers in Oncology, 2023
BRCA germline mutations in multiethnic gynecologic patients: A 10-year retrospective analysis from a single cancer institute.
Wei CH et al.
Plos One, 2023
Clinical, splicing, and functional analysis to classify BRCA2 exon 3 variants: Application of a points-based ACMG/AMP approach.
Thomassen M et al.
Human Mutation, 2022
Correction to: In-Silico analyses of Nonsynonymous Variants in the BRCA1 Gene.
Arshad S et al.
Biochemical Genetics, 2022
Human BRCA pathogenic variants were originated during recent human history.
Li J et al.
Life Science Alliance, 2022
Validation and Data-Integration of Yeast-Based Assays for Functional Classification of BRCA1 Missense Variants.
Bellè F et al.
International Journal of Molecular Sciences, 2022
Benchmarking of SpCas9 variants enables deeper base editor screens of BRCA1 and BCL2.
Sangree AK et al.
Nature Communications, 2022
Quantifying prediction of pathogenicity for within-codon concordance (PM5) using 7541 functional classifications of BRCA1 and MSH2 missense variants.
Loong L et al.
Genetics in Medicine : Official Journal of the American College of Medical Genetics, 2022
BRCA1 and Breast Cancer: Molecular Mechanisms and Therapeutic Strategies.
Fu X et al.
Frontiers in Cell and Developmental Biology, 2022
In-Silico Analyses of Nonsynonymous Variants in the BRCA1 Gene.
Arshad S et al.
Biochemical Genetics, 2021
Towards a New, Endophenotype-Based Strategy for Pathogenicity Prediction in BRCA1 and BRCA2: In Silico Modeling of the Outcome of HDR/SGE Assays for Missense Variants.
Özkan S et al.
International Journal of Molecular Sciences, 2021
Prevalence of BRCA1 and BRCA2 Mutations Among Patients With Ovarian, Primary Peritoneal, and Fallopian Tube Cancer in India: A Multicenter Cross-Sectional Study.
Gupta S et al.
Jco Global Oncology, 2021
Clinical phenotypes combined with saturation genome editing identifying the pathogenicity of BRCA1 variants of uncertain significance in breast cancer.
Wan Q et al.
Familial Cancer, 2021
Targeted Therapy of Papillary Thyroid Cancer: A Comprehensive Genomic Analysis.
Hescheler DA et al.
Frontiers in Endocrinology, 2021
Characterization of Synonymous BRCA1:c.132C>T as a Pathogenic Variant.
Li J et al.
Frontiers in Oncology, 2021
Characterization of BRCA1-deficient premalignant tissues and cancers identifies Plekha5 as a tumor metastasis suppressor.
Liu J et al.
Nature Communications, 2020
Predicting the Disease Risk of Protein Mutation Sequences With Pre-training Model.
Li K et al.
Frontiers in Genetics, 2020
REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.
Tian Y et al.
Scientific Reports, 2019
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
A Preliminary Study: Human Fibroid Stro-1+/CD44+ Stem Cells Isolated From Uterine Fibroids Demonstrate Decreased DNA Repair and Genomic Integrity Compared to Adjacent Myometrial Stro-1+/CD44+ Cells.
Prusinski Fernung LE et al.
Reproductive Sciences (thousand Oaks, Calif.), 2019
Finding driver mutations in cancer: Elucidating the role of background mutational processes.
Brown AL et al.
Plos Computational Biology, 2019
GFP-Fragment Reassembly Screens for the Functional Characterization of Variants of Uncertain Significance in Protein Interaction Domains of the BRCA1 and BRCA2 Genes.
Caleca L et al.
Cancers, 2019
Accurate classification of BRCA1 variants with saturation genome editing.
Findlay GM et al.
Nature, 2018
Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics.
Ernst C et al.
Bmc Medical Genomics, 2018
A Bayesian framework for efficient and accurate variant prediction.
Qian D et al.
Plos One, 2018
GEMO, a National Resource to Study Genetic Modifiers of Breast and Ovarian Cancer Risk in BRCA1 and BRCA2 Pathogenic Variant Carriers.
Lesueur F et al.
Frontiers in Oncology, 2018