Poster Session #1: UC Ballroom
Mathematical Modeling: A Neuroscience Case Study
Presentation Type
Poster
Faculty Mentor’s Full Name
Michael Kavanaugh
Faculty Mentor’s Department
Biomedical and Pharmaceutical Sciences
Abstract / Artist's Statement
As has been shown in recent research with by the Kavanaugh lab (Leary 2011), glutamate transporters play an important role in glutamate diffusion and signaling in the brain. The details of how the transportation process operates across spatial and temporal scales are still unknown, however. My research is in the application of computer models to help illuminate this phenomenon. By coupling dynamic models and using non-linear regression tools, I am gaining insight into the rate parameters of a multi-step, multi-molecule binding and transportation process. By combining a theoretical model from previous studies with the ability to use modern parameter fitting tools, the earlier models can be verified or improved. Additionally, this modeling process allows for the integration of multiple data sets to inform one model, which has previously been extremely challenging for these types of reactions. The presentation of this research will consist of two components: the interpretation of model results and the study of the modeling process in general. While clearly the model results are extremely important, the process of modeling real data as an undergraduate has been a good application of classroom techniques. As a mathematics major, this component is equally important to furthering my education and research skills.
Mathematical Modeling: A Neuroscience Case Study
UC Ballroom
As has been shown in recent research with by the Kavanaugh lab (Leary 2011), glutamate transporters play an important role in glutamate diffusion and signaling in the brain. The details of how the transportation process operates across spatial and temporal scales are still unknown, however. My research is in the application of computer models to help illuminate this phenomenon. By coupling dynamic models and using non-linear regression tools, I am gaining insight into the rate parameters of a multi-step, multi-molecule binding and transportation process. By combining a theoretical model from previous studies with the ability to use modern parameter fitting tools, the earlier models can be verified or improved. Additionally, this modeling process allows for the integration of multiple data sets to inform one model, which has previously been extremely challenging for these types of reactions. The presentation of this research will consist of two components: the interpretation of model results and the study of the modeling process in general. While clearly the model results are extremely important, the process of modeling real data as an undergraduate has been a good application of classroom techniques. As a mathematics major, this component is equally important to furthering my education and research skills.