My students and I study biology and pharmacology using chemical reaction engineering and data analysis. We use mathematical, statistical, and computational tools:the choice of the tool depending on the problem being studied. We also use pen-and-paper calculations and derivations ("theory") that lead to general results governing the behavior of biological systems.
Examples of the biology that we study using these methods include (a) transcription, translation and regulation at all levels from inaccessible DNA to post-translationally modified protein; (b) skin biology; (c) intracellular signaling pathways especially those in neurons; and (d) the effect of anatomy and physiology on drug delivery and effect aka QSP or 'quantitative systems pharmacology'.
Some of the tools we use are (1) theoretical analysis using the chemical master equation, or dynamical systems analysis; (2) Boolean models; (3) Continuous deterministic models (differential equations, ordinary and partial); (4) Stochastic simulations using algorithms based on the Gillespie method; (5) Chemical reaction engineering and analysis of transport and reaction, including specific use in Pharmacokinetics/Pharmacodynamics/Systems Pharmacology; and (6) Multivariate statistical methods and machine learning aka data science.
In several of these projects, work is carried out in collaboration with experimental biologists who use wet-lab techniques to study the particular process. I have worked on quantitative systems pharmacology projects with a 'big-pharma' company for >8 years, but the ~40 reports are not in the public domain.
I am constantly looking for motivated students at all levels from school to post-doctoral who are interested in this area, willing to work hard to understand both the biology and the specific mathematical/computational tool in the list above.
If interested, please look at the pull down menu to get a slightly better idea of what we do. If still interested, please write to me directly.
Disclaimer: All views expressed in this and other pages are mine and not endorsed by NCL or AcSIR. To the best of my knowledge none of these views is especially frowned upon by NCL or AcSIR.