Xinyu Bao

MUTUAL enables cross-modality analysis between transcriptome and chromatin by learning a shared RNA-ATAC space from multiome data without refitting.

This paper introduces a supervised foundation model for plant regulatory genomics that predicts chromatin state from genomic sequence, showing improved speed, accuracy, and interpretability over DNA language models.

The paper develops a general AI model that integrates diverse genomic modalities and knowledge, showing strong performance across cell types and tissues.

CelLink integrates single-cell multi-omics data by addressing weak feature linkage and imbalanced cell populations, outperforming existing methods in imputation accuracy and cell subtype annotation.