Hailing Shi

The paper introduces mcDETECT, a machine learning framework for detecting RNA granules in spatial transcriptomics data, revealing functionally distinct neuronal substates and early Alzheimer's disease pathology.

The paper introduces FuseMap, a deep-learning framework for spatial transcriptomics that creates a comprehensive molecular spatial reference atlas of the mouse brain.

This study shows that FMRP phosphorylation regulates neuronal translation via YTHDF1, revealing a mechanism for FXS pathology and suggesting YTHDF1 as a therapeutic target.

The paper creates a high-resolution spatial atlas of the mouse CNS by combining in situ sequencing with scRNA-seq data to map cell types and gene expression across the brain and spinal cord.

The paper introduces RIBOmap, a 3D in situ method to profile mRNA translation at single-cell and spatial resolutions, revealing translation dependencies on cell cycle and subcellular localization in brain tissue.

This paper introduces in situ electro-sequencing to map gene expression and electrophysiology in 3D tissues, improving cell type analysis and developmental trajectory reconstruction.

ClusterMap is a framework for analyzing spatial gene expression data, clustering RNAs into subcellular structures and tissue regions across multiple dimensions.