Jihoon Baek

BioLACE: unifying spatial geometry and marker priors for cohesive cell-type clustering in spatial transcriptomics

BioLACE improves spatial clustering in transcriptomics by integrating spatial geometry and marker gene priors within a VAE framework, achieving better cell type accuracy and interpretability.

Benchmarking clustering, alignment, and integration methods for spatial transcriptomics

This paper benchmarks clustering, alignment, and integration methods for spatial transcriptomics using real and simulated datasets, providing recommendations and code for reproducibility.