John Hughes, William O. Hancock, and John Fricks (2011). Kinesins with Extended Neck Linkers: A Chemomechanical Model for Variable-Length Stepping. Submitted toBulletin of Mathematical Biology on January 6, 2011.
Shi Chen, John Fricks, and Matthew Ferrari (2011). Tracking Measles Infection through Non-linear State Space Models. To appearJournal of the Royal Statistical Society, Series C.
John Hughes and John Fricks (2011). A Mixture Model for Quantum Dot Images of Kinesin Motor Assays. To appearBiometrics.
John Hughes, William Hancock, and John Fricks (2011). A Matrix Computational Approach to Kinesin Neck Linker Extension.Journal of Theoretical Biology. 269, No. 1, 181-194.
Ivan Simeonov, Xiaoyan Gong, Oekyung Kim, Mary Poss, Francesca Chiaromonte, and John Fricks (2010). Exploratory Spatial Analysis ofin vitro Respiratory Syncytial Virus Co-infections. Viruses. 2, No. 12, 2782-2802.
John Hughes, John Fricks, and William Hancock (2010). Likelihood Inference for Particle Location in Fluorescence Microscopy.Annals of Applied Statistics. 4, No. 2, 830-848.
I work with biological scientists to create stochastic models of biological systems. By creating dynamic models and statistical methods to link those models to data, we explore the underlying mechanisms of these systems.
I have been working with graduate student Chen Shi and assistant professor of biology Matt Ferrari to create models to predict measles cases in country wide data using knowledge of the underlying disease mechanisms.
I have also been working with an inter-disciplinary team, which includes assistant professor of biology and mathematics Tim Reluga, professor of statistics Francesca Chiaromonte, and professor of biology Mary Poss, to study the innate immune response of epithelial cells to RSV exposure. We are using both time course and spatial relationships to determine the interplay between different strains of virus.
In addition to research in disease dynamics, I study molecular motors. With Will Hancock, associate professor of bioengineering, we create models of kinesin which help us understand the mechanical effect of mutations. I am also working with Peter Kramer of RPI and Scott McKinley of the University of Florida to create models across a range of length scales, from nanometer to micron, to understand the effect of both natural regulatory factors and experimental perturbations on kinesin transport.
The image above is taken from a movie of fluorescently-tagged kinesin motors from the Hancock lab; we use these movies to study the stochastic dynamics of the motors. Similar data is used in conjunction with the Poss lab to study cell response to viral exposure.