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Quantitative Bioscience at the University of Tennessee

Quantitative Cell Biology

Cell biology image.

The cell is the basic building block of all life, but while most of the molecular components of the cell have been identified, the emergence of cell structure and behavior from molecular interactions remains a fundamentally mysterious process, as the internal workings of the cell itself take place at a mesoscale level of organization that is not accessible to direct observation. In quantitative cell biology, computer simulations, mathematical models, and quantitative measurement approaches inspired by physics are brought to bear on the question of how cells are put together and function. Quantitative cell biology uses computational and mathematical tools to describe and understand the behavior of a cell. Research also includes quantitative microscopy data acquisition and analysis from experiments. Accurate measurements are used to test predefined hypotheses in order to compare experimental data with predictions generated by theoretical models.

Researcher Department Research Interests
S. Abel photo. Steve Abel
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Chemical and Biomolecular Engineering Computational cell biology and immunology, theory and simulation of soft biological materials, membrane and polymer biophysics, systems biology
 photo. Vasilios Alexiades
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Mathematics Math biology (chemotaxis, action potentials, phototransduction), phase change processes (laser ablation, solidification), CFD, parallel computing
M. Das photo. Maitreyi Das
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Biochemistry and Cellular & Molecular Biology Study and experimental quantification of cell shape and polarity control
J. Day photo. Judy Day
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Mathematics; Electrical Engineering & Computer Science Mathematical modeling and control, dynamical systems, model predictive control, acute inflammation/immunology
S. Eda photo. Shigetoshi Eda
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Forestry, Wildlife and Fisheries; Associate Director, Center for Wildlife Health Mathematical modeling of Johne's disease epidemiology and immunology, development of an onsite diagnostic system for diseases and physiological conditions
 photo. Vitaly Ganusov
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Microbiology; Mathematics Mathematical modeling of CD8 T cell responses to acute and chronic infections
 photo. Hong Guo
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Biochemistry & Cellular and Molecular Biology Computational molecular and structural biology
T. Hong. Tian Hong
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Biochemistry and Cellular & Molecular Biology Computational systems biology
S. Lenhart. Suzanne Lenhart
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Mathematics Optimal control, population and environmental models, natural resource modeling, disease models
 photo. Vasileios Maroulas
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Mathematics Topological data analysis, applications of statistical learning methods to neuroscience and biology
RP McCord. Rachel Patton McCord
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Biochemistry & Cellular and Molecular Biology 3D genome structure and the biophysics of cell migration
 photo. Andreas Nebenführ
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Biochemistry & Cellular and Molecular Biology Cell biology of organelle movement in Arabidopsis
S. Wise. Steven Wise
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Mathematics Mathematical biology, computational materials science, computational and applied math
X. Zhao. Xiaopeng Zhao
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Mechanical, Aerospace, and Biomedical Engineering Biommedical signal processing, medical informatics, dynamics and control, computational biology



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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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