Antoine Szatkownik

This study introduces a frugal diffusion model for generating artificial genomes and evaluates its utility for local ancestry inference using synthetic and real data.

The paper generates synthetic genomes using PCA and GANs, showing improved population structure and privacy metrics compared to existing methods.

This paper introduces convolutional and conditional neural networks for generating large-scale artificial genomes with high SNP numbers while minimizing privacy leakage.

The paper introduces ASPRING, a method to detect alternatively spliced protein repeats across species, identifies over 5,000 conserved repeats, and maps them to 3D structures to study their role in protein interactions.