Pixu Shi

multiTEMPTED jointly reduces dimensionality of longitudinal multi-omic data, capturing modality-specific temporal dynamics and outperforms existing methods in speed and accuracy.

The paper develops spatially registered metabolomics and proteomics maps of rhesus monkey cortex and integrates them using novel methods to identify conserved molecular gradients and metabolic circuits.

MUSTARD reduces dimensionality of multi-sample scRNA-seq data using trajectory guidance, revealing sample-level heterogeneity and associated gene markers.

TEMPTED improves analysis of longitudinal microbiome data by incorporating time as a continuous variable, achieving high accuracy in phenotype classification and identifying microbial markers linked to birth outcomes.