Yongin Choi

The paper integrates multiple datasets to create a comprehensive human liver cell atlas, identifying new cell types and associations with demographic factors.

sciLaMA integrates gene embeddings from large language models with scRNA-seq data using a paired-VAE architecture, improving downstream tasks like batch correction and clustering while maintaining computational efficiency.

This paper introduces an interpretable variational autoencoder for genomics that identifies gene neighborhoods and hubs, revealing correlations between neuronal differentiation and mitochondrial complex co-expression.