Lingzhou Xue

Learning Perturbation Effects Through Contrastive Alignment of Multimodal Biological Embeddings

This paper introduces PertOmni, a multimodal framework that aligns transcriptomic data with text and image embeddings to improve perturbation effect prediction.

spVelo: RNA velocity inference for multi-batch spatial transcriptomics data

spVelo infers RNA velocity in multi-batch spatial transcriptomics data, showing improved velocity consistency, transition accuracy, and direction correctness compared to existing methods.

Compositional knockoff filter for high-dimensional regression analysis of microbiome data

The paper introduces a compositional knockoff filter to control false discovery rate in high-dimensional microbiome regression analysis, demonstrating improved power while maintaining FDR control.

Condition-adaptive fused graphical lasso (CFGL): an adaptive procedure for inferring condition-specific gene co-expression network

The paper introduces CFGL, a method for inferring condition-specific gene co-expression networks, showing improved accuracy and revealing biological insights in rat and cancer datasets.