Posts classified under: DBDS

Our group’s research develops artificial intelligence and machine learning algorithms to enable new capabilities in biomedicine and healthcare. We have a primary focus on computer vision, and developing algorithms to perform automated interpretation and understanding of human-oriented visual data across a range of domains and scales: from human activity and behavior understanding, to human anatomy, and human cell biology. Current projects include computer vision for extracting insights and knowledge from visual data ranging from surgery and behavioral science videos, to cell imaging data.

esearch Areas: 

• Machine/Statistical Learning
• Deep Learning
• Bioinformatics
• Computer Vision
• Medical Imaging
• Computational Biology

Current interest centers on the application of statistics to problems arsing from biology. We are particularly interested in questions concerning gene regulation and signal transduction.

Research Areas: 

• Computational Biology
• Statistics

Our goal is to use experimental and statistical tools to construct a high dimensional picture of gene regulation, including cis and trans control of the full repertoire of RNAs expressed by cells. Currently, we are focusing on the function and biogenesis of circular RNA, which we recently discovered to be a ubiquitous and uncharacterized component of eukaryotic gene expression. A second major goal is to study gene expression variation in human cancer. Here, we combine mining massive public datasets, and experimental study of primary tumors and cell lines with bioinformatic and statistical methods. We use the cancer genome as window into functional roles played by RNA, and are attempting to characterize potential biomarkers.

Research Areas: 

• Bioinformatics
• Genetics
• Machine/Statistical Learning
• Computational Biology