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Richard Bertram : GPUfit: A Tool for Real-Time Model Calibration and Prediction Testing


Mathematical modeling has become a widely-used tool for integrating
biological data, designing experiments, and ultimately understanding
biological systems. In recent years two important challenges for the
successful use of mathematical models have become apparent. One is that
models contain parameters that determine the behavior of the model, and
the values of these parameters are often hard to determine from the
available biological data. The other challenge is that many biological
systems exhibit a great deal of heterogeneity in behavior, so even if the
model parameters could be perfectly calibrated by pooling cell behaviors
to produce an “average cell model”, this model may not provide a good
description of any single cell in the population. In this seminar I will
describe a technique that we are using to integrate mathematical modeling
into experimental studies in a way that addresses both of these challenges.
We study endocrine pituitary cells that release a variety of hormones into
the blood, and our aim is to develop an approach for modeling the
behaviors of these cells with enough accuracy so that we can use the
models to make and test predictions in real time.

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