How does pollution affect the local wildlife? Can the efficacy of a drug be predicted? These questions seem ostensibly unrelated, yet both can be addressed by our team using dynamical modeling methods, tools, and models. These models are often tailor-made to address a specific question or problem, such as predicting the disposition of chemicals through an animal or the speed of a phosphorylation cascade, but can often be generalized to handle any number of different situations. As just one example, we developed a predictive model of the hypothalamus-pituitary-gonad (HPG) axis in teleost fish in partnership with the USEPA, which controls the production of reproductive hormones through complex feedback mechanisms involving phosphorylation cascades, transcriptional activation, and enzyme inhibition. This model is able accurately predict a decline in individual fecundity in response to an aromatase inhibitor pervading a freshwater ecosystem. We extended this model by including the Leslie matrix method to provide a multi-scale approach that mechanistically links molecular interactions (i.e., molecular initiating events) with population carrying capacity over long time scales, such as years and even decades. In general, our team has the broad capability to develop predictive biological models of nearly any experimental setup, from flow-through exposure tank systems and microfluidic devices to enzyme and cellular assay data, and even to larval and embryo based in vitro assays. We will model your data by leveraging any and all available data in the literature, using it to train and validate our predictive models.What can our team do for you? We can develop predictive models that test mechanism hypotheses in your research, implement known drug interactions in vivo, or even reduce your experimental costs by developing models that take limited experimental data or even eliminate it entirely by leveraging in silico “data” (e.g., QSARs). Our diverse team of computational biologists, physicists, and theoretical chemists offers mechanistic modeling capabilities in the following areas:

  • Modeling phosphorylation cascades and assay data (e.g., Western blotting)
  • Systems level (“systems biology”) models to predict serum concentrations
  • Developing mechanism based in silico dose responses for aquatic organisms
  • Single cell biochemical modeling using stochastic simulation algorithm (SSA) based methods
  • Modeling measurements made in experimental systems, such as complex microfluidics and “on-chip” tissue systems
  • Model bacterial metabolism, or “bioreactors”, at the single cell and the population level
  • Model whole bacterial colonies, both in “free media” and in confined systems such as sol-gel
  • Modeling novel material interactions between biology and inorganic substrates; i.e., biofilm growth and properties or cells and tissues embedded within viscous or solid/granular systems
  • Population modeling with stressor effects from the environment, e.g., limited food availability or predation, using agent-based computer simulation methods
  • Novel model development based on YOUR needs and projects

Contact us to discuss your specific needs and learn how we can add value to your project!