Hon Man Chan

Function-driven geometry directs human pilosebaceous unit development

The paper builds a spatiotemporal map of human pilosebaceous unit development using single-cell multiomics and machine learning, showing how epithelial-mesenchymal interactions drive organogenesis and how sebaceous gland programs are disrupted in tumors.

Multi-scale modeling of human tissues from spatial transcriptomics with TERRA

TERRA is a foundation model for spatial transcriptomics that predicts tissue behavior under perturbation and identifies multi-scale biological insights across tissues.

A multimodal interrogation of Broca's area in the pediatric and adult human brain

The paper provides a high-resolution molecular and cellular analysis of Broca's area and motor cortex across developmental stages, identifying distinct cellular signatures and vulnerabilities to neurodevelopmental disorders.

Spatial lung niches shape Pseudomonas aeruginosa persistence

This study uses spatial transcriptomics to map Pseudomonas aeruginosa niches in lung tissue from CF and COPD patients, revealing distinct bacterial states and host interactions linked to infection persistence.

Self-supervised learning for a gene program-centric view of cell states

Tripso, a self-supervised transformer model, identifies gene program-specific embeddings and discovers novel gene programs, revealing biological insights in hematopoietic development and disease.

Hidden immune memory niches in inflammatory skin diseases

This study creates a spatially-resolved molecular atlas of human skin and uses deep learning to identify 26 niches, revealing novel immune memory structures in inflammatory skin diseases.

Cutaneous T cell lymphoma atlas reveals malignant Th2 cells supported by a B cell-rich microenvironment

The paper identifies Th2-like malignant cells in CTCL supported by a B cell-rich microenvironment through single-cell and spatial transcriptomics analysis.