• Peter St. John received his B.S. in chemical engineering from Tufts University in 2010, followed by his Ph.D. in chemical engineering from the University of California at Santa Barbara in 2015. During his Ph.D., St. John applied techniques from systems biology and dynamic systems to understand the gene regulatory networks underlying mammalian circadian rhythms.

  • During his postdoctoral position, he used techniques from metabolic modeling for microbial strain design to optimize the production of value-added chemicals from lignin using Pseudomonas putida.

Featured Publications

  1. "A quantitative model for the prediction of sooting tendency from molecular structure," Energy & Fuels (2017)

  2. "Metabolic engineering of Actinobacillus succinogenes provides insights into succinic acid biosynthesis," Applied and Environmental Microbiology (2017)

  3. "Efficient estimation of the maximum metabolic productivity of batch systems," Biotechnology for Biofuels (2017)

  4. "Succinic acid production from lignocellulosic hydrolysate by Basfia succiniciproducens," Bioresource Technology (2016)

  5. "Functional network inference of the suprachiasmatic nucleus," Proceedings of the National Academy of Sciences of the United States of America (2016)

  6. "Quantifying stochastic noise in cultured circadian reporter cells," PLoS Computational Biology (2015)

  7. "Amplitude metrics for cellular circadian bioluminescence reporters," Biophysical Journal (2014)

  8. "Spatiotemporal separation of PER and CRY posttranslational regulation in the mammalian circadian clock," Proceedings of the National Academy of Sciences of the United States of America (2014)

  9. "Estimating confidence intervals in predicted responses for oscillatory biological models," BMC Systems Biology (2013)

  10. "Identification of small molecule activators of cryptochrome," Science (2012)