Systems Biology and the
Systems Molecular Basis of Disease

Traditional biology provides a biological understanding that is based upon the identification and characterization of molecular entities - e.g., genes, proteins, and mutations – that associate with biological observables.

In contrast, systems biology aims to understand how biological function results from the actions of and interactions between a collection of component molecular entities. Systems biology is a challenging, interdisciplinary, scientific ideal for which to strive.

  • Research about disease and the treatment of disease has the potential to create significant and lasting benefit to others. Lab members have enjoyed knowing that their work can, and has, impacted patient care.

    The pursuit of research is an exceptionally challenging enterprise. The potential to help others is powerful motivation when facing the challenges that come with the pursuit of discovery.

  • If systems biology aims to understand how biological function emerges from the actions and interactions of biological parts, a practitioner of the field would be well-served to study systems comprised of well-characterized parts.

    The molecular foundations of many diseases have been exceptionally well-characterized because of their medical importance; this provides the essential foundational knowledge upon which to build systems biology research.

    Additionally, a system with healthy and diseased states and with known molecular perturbations that cause the transition between states provides a meaningful set of system behaviors and determinative features upon which truly impactful methods can be developed.

  • RAS signaling plays important roles in cancer and in many other diseases. The RAS network and its molecular constituents have been exceptionally well-characterized.

    In recent years, we have combined experimental, mathematical and computational approaches to answer several different long-standing questions about RAS network behaviors in cancer and about RAS network responses to pharmaceutical treatments.