February 25, 2014 Read More →

John Abel

John Abel

PhD, Systems Biology 2018
Harvard University

T32 Trainee in Sleep, Circadian, and Respiratory Neurobiology
Harvard Medical School/Brigham and Women’s Hospital

Research

The circadian oscillator is a biological control system designed to regulate gene expression in a 24-hour periodic environment. The gene regulatory network comprising the circadian oscillator may be modeled through systems of coupled chemical reactions. Mathematically, these reactions may be described as a set of coupled nonlinear ordinary differential equations, or in some cases, as a stochastic chemical master equation. My doctoral research involves using modeling as well as dynamical systems and control theory to better understand mammalian circadian rhythms. There are two main foci within my work:

  • Understanding interactions between the genetic oscillator and electrical and chemical neurotransmission in the suprachiasmatic nucleus (collaborators: Herzog lab, WUSTL)
  • Developing algorithms and techniques for control of circadian rhythms (collaborators: Klerman lab, Harvard Medical School/Brigham and Women’s Hospital)
Education

PhD Systems Biology, Harvard University, 2018
MS Chemical Engineering, UC Santa Barbara, 2015
BS Chemical Engineering, Tufts University, 2013

Software

GillesPy: a Python package for stochastic model building and simulation
GillesPy is a modeling toolkit for discrete stochastic simulations of biochemical systems authored by myself, Brian Drawert (UCSB), Andreas Hellander (Uppsala University), and Linda Petzold (UCSB). GillesPy uses the StochKit2 solvers including the optimized direct method and tau-leaping to perform stochastic simulations. See the link above for installation instructions and examples.

Contact

johnhabel (at) g (dot) harvard (dot) edu

Publications
Dual-Color Single-Cell Imaging of the Suprachiasmatic Nucleus Reveals a Circadian Role in Network Synchrony
Yongli Shan, John H. Abel, Yan Li, Mariko Izumo, Kimberly H. Cox, Byeongha Jeong, Seung-Hee Yoo, David P. Olson, Francis J. Doyle III, & Joseph S. Takahashi. Neuron, 2020.
Pharmaceutical-based entrainment of circadian phase via nonlinear model predictive control
J. H. Abel, A. Chakrabarty, E. B. Klerman, F. J. Doyle III.  Automatica. 2019.
Entrainment of circadian rhythms depends on firing rates and neuropeptide release of VIP SCN neurons
Mazuski C, Abel JH, Chen SP, Hermanstyne TO, Jones JR, Simon T, Doyle FJ, Herzog ED. Entrainment of circadian rhythms depends on firing rates and neuropeptide release of VIP SCN neurons. Neuron, 2018. doi:10.1016/j.neuron.2018.06.029
Controlling Biological Time: Nonlinear Model Predictive Control for Populations of Circadian Oscillators
J. H. Abel, A. Chakrabarty, and F. J. Doyle III. “Controlling Biological Time: Nonlinear Model Predictive Control for Populations of Circadian Oscillators.” in Emerging Applications of Control and Systems Theory, R. Tempo, S. Yurkovich, and P. Misra, Editors, Springer, 2018.
Ontogeny of circadian rhythms and synchrony in the suprachiasmatic nucleus
V Carmona-Alcocer, JH Abel, TC Sun, LR Petzold, FJ Doyle III, CL Simms, ED Herzog. “Ontogeny of circadian rhythms and synchrony in the suprachiasmatic nucleus,” Journal of Neuroscience, 2017. doi:10.1523/JNEUROSCI.2006-17.2017
GillesPy: a Python package for stochastic model building and simulation
J.H. Abel, B. Drawert, A. Hellander, and L.R. Petzold, “GillesPy: a Python package for stochastic model building and simulation,” IEEE Life Sciences Letters, 2017. doi: 10.1109/LLS.2017.2652448
A systems theoretic approach to analysis and control of mammalian circadian dynamics
J.H. Abel and F.J. Doyle III. “A systems theoretic approach to analysis and control of mammalian circadian dynamics.” Chemical Engineering Research and Design, 2016. doi:10.1016/j.cherd.2016.09.033
Functional network inference of the suprachiasmatic nucleus
J.H. Abel, K. Meeker, D. Granados-Fuentes, P.C. St. John, T.J. Wang, B.B. Bales, F.J. Doyle III, E.D. Herzog, L.R. Petzold. “Functional network inference of the suprachiasmatic nucleus.” Proceedings of the National Academy of Sciences of the United States of America, 113(16), 2016. doi:10.1073/pnas.1521178113
A Coupled Stochastic Model Explains Differences in Cry Knockout Behavior
J.H. Abel, L.A. Widmer, P.C. St. John, J. Stelling, and F.J. Doyle III, ” A Coupled Stochastic Model Explains Differences in Cry Knockout Behavior.” IEEE Life Sciences Letters, Jun 2015. doi:10.1109/LLS.2015.2439498
Amplitude metrics for cellular circadian bioluminescence reporters
P.C. St John, S.R. Taylor, J.H. Abel, F.J. Doyle III, “Amplitude metrics for cellular circadian bioluminescence reporters,” Biophysical Journal, vol. 107, no. 11, pp. 2712-22,Dec 2014. [DOI]
Porosity-Tuned Chitosan-Polyacrylamide Hydrogel Microspheres for Improved Protein Conjugation.
S. Jung, J.H. Abel, Starger, H. Yi, Biomacromolecules, 2016. DOI: 10.1021/acs.biomac.6b00582.
Shape-Encoded Chitosan-Polyacrylamide Hybrid Hydrogel Microparticles with Controlled Macroporous Structures via Replica Molding for Programmable Biomacromolecular Conjugation.
E. Kang, S. Jung, J.H. Abel, A. Pine, H. Yi, Langmuir, 32(21): 5394-402, 2016. doi: 10.1021/acs.langmuir.5b04653
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