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Germ-Line Mutation

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Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm.

Cancer medicine
Many breast cancer (BC) patients treated with aromatase inhibitors (AIs) develop aromatase inhibitor-related arthralgia (AIA). Candidate gene studies to identify AIA risk are limited in scope. We evaluated the potential of a novel analytic algorithm ...

Machine learning-based reclassification of germline variants of unknown significance: The RENOVO algorithm.

American journal of human genetics
The increasing scope of genetic testing allowed by next-generation sequencing (NGS) dramatically increased the number of genetic variants to be interpreted as pathogenic or benign for adequate patient management. Still, the interpretation process oft...

Thousands of induced germline mutations affecting immune cells identified by automated meiotic mapping coupled with machine learning.

Proceedings of the National Academy of Sciences of the United States of America
Forward genetic studies use meiotic mapping to adduce evidence that a particular mutation, normally induced by a germline mutagen, is causative of a particular phenotype. Particularly in small pedigrees, cosegregation of multiple mutations, occasiona...

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

Genome medicine
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...

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

International journal of molecular sciences
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...

Predicting mutational function using machine learning.

Mutation research. Reviews in mutation research
Genetic variations are one of the major causes of phenotypic variations between human individuals. Although beneficial as being the substrate of evolution, germline mutations may cause diseases, including Mendelian diseases and complex diseases such ...

Discovering predisposing genes for hereditary breast cancer using deep learning.

Briefings in bioinformatics
Breast cancer (BC) is the most common malignancy affecting Western women today. It is estimated that as many as 10% of BC cases can be attributed to germline variants. However, the genetic basis of the majority of familial BC cases has yet to be iden...