David Umulis

David Umulis

Dane A. Miller Head and Professor, Biomedical Engineering/Professor, Agricultural & Biological Engineering
Purdue University
Department of Agricultural & Biological Engineering
225 South University Street
West Lafayette, IN 47907-2093
Office: MJIS 3001

Areas of Interest

  • Biological Engineering

Research Areas

Systems Biology. Interdisciplinary research: mechanisms of development and regulation of Bone Morphogenetic Proteins. Finite-element modeling of biological systems. Quantitative image analysis, microscopy, and data-driven modeling. https://engineering.purdue.edu/~dumulis

Biography

Transforming growth factor-Beta (TGF-Beta) pathways regulate many cellular processes in human development. Mutations in the Bone Morphogenetic Proteins (BMPs), a TGF-Beta family member, can lead to a number of diseases including cancer, vascular disease, congenital heart disease, and juvenile polyposis syndrome (JPS), a genetic disorder which greatly increases the risk for developing gastrointestinal cancer. BMP pathways provide a natural candidate for drug development, however the complex mechanisms of BMP regulation and cross-talk with other signaling pathways such as the map-kinase pathway preclude our ability to understand, let alone predict, the relationship between a change in BMP activity and the downstream effects. Future treatment of cancer, genetic, and developmental disorders will require a more quantitative, systems-level approach aided by sophisticated models that directly couple tissue geometry, molecular mechanisms, and other information-rich data sets.

My lab focuses on microscopy, image analysis, and finite-element computer modeling to elucidate mechanisms of BMP regulation by developing organism- and tissue-scale, data-driven models of Drosophila embryos, Xenopus embryos, and the epithelial layers of the Drosophila wing imaginal disc. While there is no substitute for hypothesis testing by experimentation, the organism-scale models provide a new methodology to conduct large-scale screens to test plausible regulatory mechanisms and identify conditions that lead to easily discernable phenotypes. We are uniquely capable of developing the models, conducting the model-driven screens, and testing the model predictions by experimentation and biological imaging.

Publication reprints available upon request or my Google Scholar page.