AIMC Topic: BRCA1 Protein

Clear Filters Showing 1 to 9 of 9 articles

A random forest-based predictive model for classifying BRCA1 missense variants: a novel approach for evaluating the missense mutations effect.

Journal of human genetics Apr 18, 2025
The right classification of variants is the key to pre-symptomatic detection of disease and conducting preventive actions. Since BRCA1 has a high incidence and penetrance in breast and ovarian cancers, a high-performance predictive tool can be employ...
Machine Learning Female Breast Neoplasms Humans Ovarian Neoplasms Random Forest Mutation, Missense BRCA1 Protein ROC Curve Genetic Predisposition to Disease Computational Biology
View on PubMed DOI

Deep Learning for Detecting BRCA Mutations in High-Grade Ovarian Cancer Based on an Innovative Tumor Segmentation Method From Whole Slide Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc Aug 12, 2023
BRCA1 and BRCA2 genes play a crucial role in repairing DNA double-strand breaks through homologous recombination. Their mutations represent a significant proportion of homologous recombination deficiency and are a reliable effective predictor of sens...
BRCA1 Protein Female BRCA2 Protein Deep Learning Ovarian Neoplasms Humans Mutation Carcinoma, Ovarian Epithelial Poly(ADP-ribose) Polymerase Inhibitors
View on PubMed DOI

Mastectomy with Reconstruction Including Robotic Endoscopic Surgery (MARRES): a prospective cohort study of the Korea Robot-Endoscopy Minimal Access Breast Surgery Study Group (KoREa-BSG) and Korean Breast Cancer Study Group (KBCSG).

BMC cancer Jun 21, 2023
BACKGROUND: Robotic nipple-sparing mastectomy (RNSM) has emerged as a new treatment option for breast cancer and risk-reducing mastectomy (RRM) for women who have a high risk of pathogenic variants. Even though several studies have reported that RNSM...
Retrospective Studies Republic of Korea Female Humans Prospective Studies Cohort Studies Robotics Robotic Surgical Procedures Adult Endoscopy Breast Neoplasms BRCA1 Protein Mastectomy BRCA2 Protein Mammaplasty Nipples
View on PubMed DOI

Artificial intelligence-based recognition for variant pathogenicity of BRCA1 using AlphaFold2-predicted structures.

Theranostics Jan 1, 2023
With the surge of the high-throughput sequencing technologies, many genetic variants have been identified in the past decade. The vast majority of these variants are defined as variants of uncertain significance (VUS), as their significance to the fu...
BRCA1 Protein Humans Artificial Intelligence Genetic Predisposition to Disease Virulence Amino Acid Sequence
View on PubMed DOI

Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.

International journal of molecular sciences Sep 26, 2022
BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessment is not sufficient to identify all patients with genomic instability, since BRCA 1/2 mutations ar...
BRCA1 Protein Eosine Yellowish-(YS) Hematoxylin Germ-Line Mutation Ovarian Neoplasms Mutation Carcinoma, Ovarian Epithelial Humans Female Deep Learning
View on PubMed DOI

Detection of Breast Cancer Lump and BRCA1/2 Genetic Mutation under Deep Learning.

Computational intelligence and neuroscience Sep 19, 2022
To diagnose and cure breast cancer early, thus reducing the mortality of patients with breast cancer, a method was provided to judge threshold of image segmentation by wavelet transform (WT). It was used to obtain information about the general area o...
Mutation High-Throughput Nucleotide Sequencing BRCA1 Protein Female Breast Neoplasms Deep Learning Humans
View on PubMed DOI

DrABC: deep learning accurately predicts germline pathogenic mutation status in breast cancer patients based on phenotype data.

Genome medicine Feb 25, 2022
BACKGROUND: Identifying breast cancer patients with DNA repair pathway-related germline pathogenic variants (GPVs) is important for effectively employing systemic treatment strategies and risk-reducing interventions. However, current criteria and ris...
Humans BRCA1 Protein Mutation BRCA2 Protein Breast Neoplasms Phenotype Germ Cells Female Deep Learning DNA Repair Genetic Predisposition to Disease Germ-Line Mutation
View on PubMed DOI

New Approach for Risk Estimation Algorithms of Negativeness Detection with Modelling Supervised Machine Learning Techniques.

Disease markers Dec 9, 2020
gene testing is a difficult, expensive, and time-consuming test which requires excessive work load. The identification of the gene mutations is significantly important in the selection of treatment and the risk of secondary cancer. We aimed to deve...
BRCA1 Protein BRCA2 Protein Breast Neoplasms Genetic Testing Supervised Machine Learning Humans Female
View on PubMed DOI

Molecular and epigenetic profiles of BRCA1-like hormone-receptor-positive breast tumors identified with development and application of a copy-number-based classifier.

Breast cancer research : BCR Jan 25, 2019
BACKGROUND: BRCA1-mutated cancers exhibit deficient homologous recombination (HR) DNA repair, resulting in extensive copy number alterations and genome instability. HR deficiency can also arise in tumors without a BRCA1 mutation. Compared with other ...
Receptors, Estrogen Epigenomics Homologous Recombination Receptors, Progesterone Datasets as Topic Adult Support Vector Machine Humans BRCA1 Protein Breast Neoplasms Female DNA Copy Number Variations DNA Methylation CpG Islands Middle Aged Aged Breast Promoter Regions, Genetic Survival Analysis
View on PubMed DOI
Popular Topics
Recent Journals