Large-scale clinical interpretation of genetic variants using evolutionary data and deep learning
Quantifying the pathogenicity of protein variants in human disease-related genes would
have a profound impact on clinical decisions, yet the overwhelming majority (over 98%) of …
have a profound impact on clinical decisions, yet the overwhelming majority (over 98%) of …
Disease variant prediction with deep generative models of evolutionary data
Quantifying the pathogenicity of protein variants in human disease-related genes would
have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of …
have a marked effect on clinical decisions, yet the overwhelming majority (over 98%) of …
[HTML][HTML] Deep generative modeling of the human proteome reveals over a hundred novel genes involved in rare genetic disorders
Identifying causal mutations accelerates genetic disease diagnosis, and therapeutic
development. Missense variants present a bottleneck in genetic diagnoses as their effects …
development. Missense variants present a bottleneck in genetic diagnoses as their effects …
Bayesian models for syndrome-and gene-specific probabilities of novel variant pathogenicity
Background With the advent of affordable and comprehensive sequencing technologies,
access to molecular genetics for clinical diagnostics and research applications is increasing …
access to molecular genetics for clinical diagnostics and research applications is increasing …
Cross-protein transfer learning substantially improves disease variant prediction
Background Genetic variation in the human genome is a major determinant of individual
disease risk, but the vast majority of missense variants have unknown etiological effects …
disease risk, but the vast majority of missense variants have unknown etiological effects …
Updated benchmarking of variant effect predictors using deep mutational scanning
BJ Livesey, JA Marsh - Molecular systems biology, 2023 - embopress.org
The assessment of variant effect predictor (VEP) performance is fraught with biases
introduced by benchmarking against clinical observations. In this study, building on our …
introduced by benchmarking against clinical observations. In this study, building on our …
3Cnet: pathogenicity prediction of human variants using multitask learning with evolutionary constraints
Motivation Improvements in next-generation sequencing have enabled genome-based
diagnosis for patients with genetic diseases. However, accurate interpretation of human …
diagnosis for patients with genetic diseases. However, accurate interpretation of human …
Biomedical informatics and machine learning for clinical genomics
While tens of thousands of pathogenic variants are used to inform the many clinical
applications of genomics, there remains limited information on quantitative disease risk for …
applications of genomics, there remains limited information on quantitative disease risk for …
DeMAG predicts the effects of variants in clinically actionable genes by integrating structural and evolutionary epistatic features
Despite the increasing use of genomic sequencing in clinical practice, the interpretation of
rare genetic variants remains challenging even in well-studied disease genes, resulting in …
rare genetic variants remains challenging even in well-studied disease genes, resulting in …
Varipred: Enhancing pathogenicity prediction of missense variants using protein language models
Computational approaches for predicting the pathogenicity of genetic variants have
advanced in recent years. These methods enable researchers to determine the possible …
advanced in recent years. These methods enable researchers to determine the possible …