報告題目：Exploring cell organization in spatial omics with machine learning
報告人：Juexin Wang, Indiana University-Purdue University, USA
報告時間：2024年7月1日 14:00-15:00
報告地點：數學樓第一報告廳
校内聯系人：徐旭 xuxu@jlu.edu.cn
報告摘要：Emerging spatial omics provides unprecedented challenges and opportunities for bioinformatic research. Here I present three recent works in my lab: (1) BSP, a dimension-agnostic granularity-based spatially variable gene identification approach, and scBSP, a computational efficient implementation of BSP; (2) REGNN, an empowered graph neural networks for heterogeneous tissue architecture analysis in kidney; and (3) TrimNN, a triangulation structural motif neural network for identifying cell organization in spatial omics.
報告人簡介：Dr. Wang is an Assistant Professor in the Department of BioHealth Informatics at Indiana University-Purdue University Indianapolis. He earned his PhD in Computer Science in Jilin University and finished his training in Bioinformatics at the University of Missouri. His research mainly focuses on developing computational methods to model single-cell and spatial transcriptomics data, and data analysis in kidney diseases, cancer, and nervous system diseases. His lab has been funded by NIH.
