News

Excited to share our latest #genomics work published in Nature Methods. MISO (MultI-modal Spatial Omics) is a versatile algorithm for feature extraction and clustering, capable of integrating multiple modalities from diverse spatial omics experiments with high spatial resolution. Its effectiveness is demonstrated across various datasets, encompassing gene expression, protein expression, epigenetics, metabolomics and tissue histology […]

Congratulations to Chenyang Yuan on winning 1st place in the Patel-Naik Award! This achievement is particularly impressive given the highly competitive nature of the award, with many of the contenders being senior BIOS Ph.D. students.

Dr. Hu presented on multi-layered applications of AI for detailed study of tumor microenvironments.  Link

Excited to share our new article on building and evaluating METI, an end-to-end framework for deep profiling of tumor ecosystems using spatial transcriptomics. We’ve built on our previous success in creating super-resolution gene expression images, combined with advances in interpretable computational pathology, to enable METI to map cancer cells and TME components, stratify cell types […]

I recently had the opportunity of being interviewed by SEQanswers, where I delved into the transformative power of Artificial Intelligence in the world of medicine. We’re standing on the brink of a healthcare revolution, and I’m thrilled to share my perspectives on how AI is reshaping our approach to medical challenges, diagnosis, and treatment Link […]

Congratulations to Jing Huang on winning 1st place in the Patel-Naik Award! This achievement is particularly impressive given the highly competitive nature of the award, with many of the contenders being senior BIOS Ph.D. students.

Posters presented by lab members: Chenyang Yuan: Integration of label-free, interpretable image features with spatial molecular profiles.(PB5093) Yefeng Yang: Efficient quantification of pattern similarity between spatial genomics and cell morphology. (PB3369)

The meeting will include presentations from renowned speakers on recent developments and applications of deep learning models in bioinformatics, genomics, and structural biology, as well as interactive workshops and networking. Link: 2023 IOB Symposium

Congratulations on our groundbreaking collaborative publication in Nature Medicine: “Pan-cancer T cell atlas reveals crucial cellular stress response state associated with immunotherapy resistance.” In this remarkable study, we have successfully identified a unique stress response state, TSTR, characterized by heat shock gene expression. TSTR cells are detectable in situ in the tumor microenvironment across various […]

Glad to share our latest publication in Cell Systems. We developed a method named TESLA, which is a spatially-resolved transcriptomics data analysis tool for integrates gene expression and histology to annotate tumor microenvironment at super-resolution. Link: https://doi.org/10.1016/j.cels.2023.03.008