This action funds an NSF Postdoctoral Research Fellowship in Biological Informatics for FY 2005. The fellowship supports research and training at the postdoctoral level at the intersection of biology and the informational, computational, mathematical, and statistical sciences. The goal of the fellowship is to provide training to a young scientist in preparation for a career in biological informatics in which research and education will be integrated. There is an increasing need for training in biological informatics at all occupational levels, and it is expected that Fellows trained through these fellowships will play important roles in training the future workforce.
The research and training plan for this fellowship is entitled "Development and use of statistical learning tools for assessing models of neural spiking." Statistical learning tools, such as boosting, are used for a wide variety of bioinformatics applications. This research is developing both general purpose statistical learning tools and tools specifically designed to assess the assumptions inherent in models for visual neuroscience. These tools are designed for use in the study of the input-output relationship of neurons in the visual cortex or the retina.
The training goal is to learn the biology underlying how the brain processes visual information, through weekly lab meetings, lectures, classes, and conferences. Collaborations are being established with experimentalists at neighboring labs at the NYU Center for Neural Science, as well as applied mathematicians at the Courant Institute and Princeton University. Broader impacts include working with the Program for Women in Mathematics at the IAS.
