Excited to share our new review paper: Statistical and machine learning methods for spatially resolved transcriptomics with histology doi.org/10.1016/j.csbj…

My shining personal webpage is online! sites.google.com/view/drjianhu/

Glad to share my latest publication in Nature Methods. We developed a method named SpaGCN, which is a spatially-resolved transcriptomics data analysis tool for identifying spatial domains and spatially variable genes using graph convolutional networks. nature.com/articles/s4159…

Check out my lab website!😃😃😃 jianhu-lab.org

Glad to share my latest publication with Mingyao Li in Cell Systems. TESLA is a spatially-resolved transcriptomics data analysis tool for integrates gene expression and histology to annotate tumor microenvironment at super-resolution. doi.org/10.1016/j.cels…

.Jian Hu et al. present a ML framework for integration of histological and spatial gene expression data to annotate heterogeneous immune and tumor cells directly in histology images and increase the resolution of the ST data. Mingyao Li Linghua Wang, MD, PhD cell.com/cell-systems/f…

⚡️📣 Excited to share our new article on METI, a framework for deep profiling of tumor ecosystems using spatial transcriptomics. Check it out! 🔗 Article: [Nature Communications](nature.com/articles/s4146…) 🔗 GitHub: [METI](github.com/Flashiness/METI) Congratulations to Linghua Wang, MD, PhD !

⚡️📣 Building on our success in creating super-resolution gene expression images, we've developed METI to identify key tumor microenvironment components. Check it out at: nature.com/articles/s4146… Congratulations to Linghua Wang, MD, PhD , Jiahui, everyone else contributed to this work!

We were thrilled to host Dr. Jian Hu Jian Hu from Emory last week, where he presented on multi-layered applications of AI for detailed study of tumor microenvironments. Thanks so much for coming to UNC!

Excited to share our latest #genomics work led by Mingyao Li published in Nature Methods! MISO integrates multiple modalities from diverse spatial omics experiments to identify biologically meaningful spatial domains. nature.com/articles/s4159…

Our latest work in Nature Communications! 🎇 MorphLink identifies and visualizes disease-relevant molecular–morphology interplay. Congrats to Jing Huang at Emory Genetics, and many thanks to Linghua Wang, MD, PhD’s team at MD Anderson for the great collaboration! 🔗 nature.com/articles/s4146…