Adrienne Roeder, Cornell University
Assistant Professor
Ithaca, New York
ahr75@cornell.edu
Office:
(607) 255-4467
Expert In
Bio/Research
I am fascinated by how beautiful and complex patterns form during development. The patterning process generally requires that one cell adopts a different identity from its neighbor. Patterns are generally formed while the cells are growing and dividing, yet the coordination of cell division and g...
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Bio/Research
I am fascinated by how beautiful and complex patterns form during development. The patterning process generally requires that one cell adopts a different identity from its neighbor. Patterns are generally formed while the cells are growing and dividing, yet the coordination of cell division and growth with the process of patterning is only beginning to be understood. In plants, regulation of cell division is crucial for proper development because plant cells cannot move or even slip relative to one another. I am interested in how growth and cell division themselves contribute to the both the development and patterning of specialized cell types in plants - a process which requires analysis of development in space and time. My laboratory uses a new, three pronged computational morphyodynamics approach that helps biologists understand how development occurs in space and time. First, we use a confocal microscope to image the living plant so that we can observe how cells grow and divide, as well as how gene expression patterns change in time during development. Every 6 hours we take the plant out of the growth room, put it on the microscope, take an image, and return the plant to the growth room. Second, we collaborate with image processing experts, who develop software that automatically detects features in the images such as nuclei and plasma membranes. For example, we can determine the number and size distribution of a population of cells. Finally, we use computational modeling to examine the consequences of our hypotheses in time. We compare our model to the live imaging data to see whether the model recreates the development of the plant. The models help us to refined hypotheses and design new experiments to test them.
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