Accepting New Students
Yes
Project Accepting Students
- Application of Spatial Transcriptomics to Study Cancer Microenvironments
- Project Description: This project involves using spatial transcriptomics (ST) data to understand transcriptional regulation in cancer tissues. The focus will be on integrating multi-omics data to predict transcription factor activity and how it shapes tumor progression and immune response.
- Machine Learning Approaches for Predicting Cellular Behavior in Disease
- Project Description: In this project, we will apply machine learning algorithms to predict cellular fate and behavior in diseases like cancer and end stage liver and kidney diseases. Students will work with large-scale single-cell and spatial transcriptomics datasets.
Program 1
Program 1 Research Interests
My research focuses on understanding how cellular processes are regulated at the molecular level, particularly in complex tissues. We use multi-omics technologies, including single-cell sequencing and spatial transcriptomics, combined with machine learning approaches to uncover the transcriptional networks that govern cell identity, disease progression, and cellular interactions in both normal and pathological states. My work spans cancer genomics, precision medicine, and the molecular basis of complex diseases such as end stage liver diseases.
Department Webpage:
https://www.osmanbeyoglulab.com/
Program 1 Faculty Information