How to Model for a Living: The CSGF as a Catalyst for Supermodels

Models are ubiquitous and uniting tools for computational scientists across disciplines. As a computational biophysical chemist, I apply multiple models to understand and predict how molecules recognize and interact with each other in complex, dynamic biological environments. The Department of Energ...

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Published inComputing in science & engineering Vol. 23; no. 6; pp. 34 - 41
Main Author Radhakrishnan, Mala L.
Format Journal Article
LanguageEnglish
Published United States IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Biological system modeling
Computational modeling
Context modeling
Electrostatics
Mathematical models
Predictive models
Scientists
Software
Solvents
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Summary:Models are ubiquitous and uniting tools for computational scientists across disciplines. As a computational biophysical chemist, I apply multiple models to understand and predict how molecules recognize and interact with each other in complex, dynamic biological environments. The Department of Energy Computational Science Graduate Fellowship (DOE CSGF) cultivates interest in engaging in models from an multidisciplinary perspective and enables junior scientists to see how computational modeling is a creative and collaborative process. In the following, I describe ways, based in part on my own experiences as a CSGF recipient, in which modeling can be used both to understand the molecular world and to excite others about computational science.
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Mala L. Radhakrishnan is currently a Professor in the Chemistry Department at Wellesley College. She received her Ph.D. in Physical Chemistry from MIT and was a recipient of the DOE CSGF in 2004 and the Howes Scholar Award in 2008. In addition to publishing in the field of molecular recognition, she is interested in both science communication and pedagogy and has written two books of poetry aimed to communicate concepts in chemistry to a broader audience.
ISSN:1521-9615
1558-366X
DOI:10.1109/MCSE.2021.3119764