Early Career Profile: Melissa A. St. Hilaire

What she does:

Melissa's work focuses on sleep research in humans, with an emphasis on sleep studies designed to understand the basic physiology of sleep and circadian rhythms. The main function of a Biomathematical Programmer Analyst in the Biomathematical Modeling Unit within the Division of Sleep Medicine is to develop and refine physiologically-based mathematical models of the human circadian pacemaker and to create software applications to simulate these models. These models are used to understand the essential features of the circadian system, including interactions between sleep and the circadian system, to make predictions for new experimental protocols and to generate new hypotheses to be tested experimentally. The development and refinement of mathematical models involves incorporation of available experimental data to continuously update and validate the model predictions against experimental findings. This requires interaction and collaboration between the Biomathematical Modeling Unit and the scientific investigators who run the experiments.

Math on the job:

Math is an integral part of the Biomathematical Programmer Analyst position. To incorporate experimental data into a mathematical model, it is necessary to clean and analyze the data using various statistical techniques. Excel, SAS and Matlab are frequently used for these purposes. The development of equations to describe the circadian system requires knowledge of both the physiology underlying the circadian system and classes of model equations that can be used to describe the system. Once a model equation has been chosen, it is necessary to estimate the parameters that will fit the model to the experimental data with minimal error. Nonlinear optimization procedures programmed into Matlab are often utilized to find the maximum likelihood estimate of each parameter. Statistics such as the Akaike Information Criterion are used to determine the goodness of fit of the model to the data. As a final step, the model must be validated on an independent data set to test the robustness of the model predictions.

Melissa's background:

Melissa recently obtained a Master's degree in Bioinformatics. She attends both weekly and annual conferences to stay current with advances in the field of sleep and circadian rhythms and also present her own findings.

Advice to students:

There is an increasing need for the application of mathematics in many different fields. It is to a student's advantage to have a solid understanding of mathematics, statistics and computer science. Also, Melissa suggests that students would benefit with knowledge of another major field, such as biology or chemistry. Furthermore, an interesting and challenging undergraduate project can open doors to many possible job opportunities and learning experiences.

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Last modified: September 25, 2006 11:24:11