Christopher Heje Grønbech

This paper introduces a deep learning method using variational autoencoders to improve microbial genome binning from metagenomic data, achieving higher precision and completeness in reconstructed bins.

scVAE is a variational auto-encoder for scRNA-seq data that avoids preprocessing and improves clustering by using raw counts and latent space clustering.