Lab Home | Phone | Search
Center for Nonlinear Studies  Center for Nonlinear Studies
 Colloquia Archive 
 Postdoc Seminars Archive 
 Quantum Lunch 
 Quantum Lunch Archive 
 CMS Colloquia 
 Q-Mat Seminars 
 Q-Mat Seminars Archive 
 P/T Colloquia 
 Kac Lectures 
 Kac Fellows 
 Dist. Quant. Lecture 
 Ulam Scholar 
 CNLS Fellowship Application 
 Student Program 
 Past Visitors 
 History of CNLS 
 Maps, Directions 
 CNLS Office 
Zachary R Fox

CNLS Postdoctoral Research Associate

Systems Biology and Biophysics

Zachary R Fox

Office: TA-3, Bldg 1690
Mail Stop: B258
home page

Research highlight
 Educational Background/Employment:
  • BBE (2014) Bioengineering, University of Delaware
  • Ph.D. (2019) Bioengineering, Colorado State University
  • Professional Training:
    • 2019-2020 Postdoctoral Researcher in Applied Mathematics and Cybergenetics at Institut Pasteur in Paris, France.

Research Interests:

  • Learning models and parameters from modern single-cell microscopy data.
  • Quantitative analysis of single-cell microscopy data.
  • Mathematical analysis of random walks.

Selected Recent Publications:

  1. Jashnsaz, Fox, Hughes, Li, Munsky, Neuert. Diverse cell stimulation kinetics identify predictive signal transduction models, iScience. 23, 10 (2020).
  2. Fox, Neuert, Munsky. Optimal Design of Single-Cell Experiments within Temporally Fluctuating Environments., Complexity. 2020, Article ID 8536365 (2020).
  3. Aguilera, Raymond, Fox, May, Djokic, Morisaki, Stasevich, Munsky. Computational design and interpretation of single-RNA translation experiments., PloS Computational Biology. 15(10), (2019).
  4. Fox and Munsky. The finite state projection based Fisher information matrix approach to estimate and maximize the information in single-cell experiments., PloS Computational Biology. 15(1), (2019).
  5. Vo, Fox, Baetica, Munsky. Bayesian estimation for stochastic gene expression using multifidelity models., Journal of Physical Chemistry B. 123(10), 2217-2234 (2019).
  6. Munsky, Li, Fox, Shepherd, Neuert. Distribution shapes govern the discovery of predictive models for gene regulation., Proceedings of the National Academy of Sciences. 123(10), 2217-2234(2018).
LANL Operated by the Triad National Security, LLC for the National Nuclear Security Administration of the US Department of Energy.
Copyright © 2003 LANS, LLC | Disclaimer/Privacy