Uwe Ohler's Research Group
John Doe
Email: daniel.mace (at) duke.edu
Location: CIEMAS 2211
Hometown: Niantic, CT
Research Interests
Systems biology, factor graphs, multiscale modeling
Thesis Work
My thesis work is largely focused on developing methodologies for extracting and modeling systems biology data from microscopy images and can be broken down into two main categories: image processing, and spatial statistical modeling. My image processing research involves developing methodologies for extracting and quantifying spatial expression data from developing organisms. By using image registration methods in combination with statistical shape models, we have developed fully automated methods for Drosophila and Arabidopsis that allow us to process and quantify spatial expression patterns for tens of thousands of images across several thousand genes. The primary interests of my research lie in the modeling of the quantifed data. Expression data from confocal images provide a rich data source with spatial and temporal resolution that would otherwise be uncapable with microarrays. Developing models that describe these spatiotemporal dependencies will allow us to describe developing gene interactions on a much finer scale.
Education
Pace University
Bachelor of Science in Computer Science
Bachelor of Science in Mathematics, concentration Biology
Outside Interests/Hobbies
Scuba diving, traveling