Deep convolutional and conditional neural networks for large-scale genomic data generation

Learning a restricted Boltzmann machine using biased Monte Carlo sampling

(2023) Nicolas Béreux et al.   SciPost Physics

An Overview of Deep Generative Models in Functional and Evolutionary Genomics

(2023) Burak Yelmen et al.   Annual Review of Biomedical Data Science

A deep learning framework for characterization of genotype data

(2022) Kristiina Ausmees et al.   G3-Genes Genomes Genetics

Privacy preserving Generative Adversarial Networks to model Electronic Health Records

(2022) Rohit Venugopal et al.   NEURAL NETWORKS

Visualizing population structure with variational autoencoders

(2021) C J Battey et al.   G3-Genes Genomes Genetics

Creating artificial human genomes using generative neural networks

(2021) Burak Yelmen et al.   PLoS Genetics

Automatic inference of demographic parameters using generative adversarial networks

(2021) Zhanpeng Wang et al.   Molecular Ecology Resources

VEGA is an interpretable generative model for inferring biological network activity in single-cell transcriptomics

(2021) Lucas Seninge et al.   Nature Communications

Generation and evaluation of privacy preserving synthetic health data

(2020) Andrew Yale et al.   NEUROCOMPUTING

Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci

(2020) Hannah L. Nicholls et al.   Frontiers in Genetics

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

(2020) Fabian Isensee et al.   NATURE METHODS

Impact of HIPAA’s minimum necessary standard on genomic data sharing

(2017) Barbara J Evans et al.   GENETICS IN MEDICINE

A global reference for human genetic variation

(2015) Richard A. Gibbs et al.   NATURE

Differentially private genome data dissemination through top-down specialization

(2014) Shuang Wang et al.   BMC Medical Informatics and Decision Making