AIMC Topic: Genes, BRCA1

Clear Filters Showing 1 to 2 of 2 articles

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

American journal of human genetics Mar 23, 2021
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...
Humans Machine Learning Reproducibility of Results Datasets as Topic Germ-Line Mutation Computer User Training Genes, BRCA1
View on PubMed DOI

Integrating pharmacophore model and deep learning for activity prediction of molecules with BRCA1 gene.

Journal of bioinformatics and computational biology Feb 1, 2024
In this paper, we propose a novel approach for predicting the activity/inactivity of molecules with the BRCA1 gene by combining pharmacophore modeling and deep learning techniques. Initially, we generated 3D pharmacophore fingerprints using a pharmac...
Reproducibility of Results Drug Discovery Deep Learning Genes, BRCA1 Pharmacophore
View on PubMed DOI
Popular Topics
Recent Journals