Modeling, analysis, and discovery of Bone Morphogenetic Protein (BMP) signaling networks in Drosophila stem cell maintenance and embryo development. The spatiotemporal regulation of Bone Morphogenetic Protein (BMP)-mediated cell differentiation relies on numerous secreted molecules and feedback networks that modify both the extracellular morphogen distribution and an individual cell's receptivity to the morphogen signal. To investigate coupled intra/extracellular BM-mediated patterning, the Umulis lab is developing computational models of the Drosophila embryo and germarium to identify mechanism of pattern reproducibility, scale-invariance, and homeostasis. In the germarium model, the Umulis group is focusing on mechanisms by which positive feedback enhances Dpp (Drosophila BMP2/4) uptake by Germline Stem Cells (GSCs), to determine mechanisms of autoregulation of stem cell number by competition for Dpp. In the embryo model for dorsal/ventral patterning Dr. Umulis is focusing on the identification of the positive feedback mechanism based on the use of biological image data for model design and optimization.
Development of new methods for data/model integration in biological engineering. Biological engineering is a relatively new engineering discipline focused on utilizing cellular and biomolecular processes to address problems related to human health, biofuels, and the environment. The types of problems encountered at the interface between biology and engineering are unique relative to those encountered in other engineering disciplines because the data available and obtainable is not strictly quantitative and cannot be described in terms of the four fundamental dimensions of length, temperature, time and mass. Instead, the available biological data provides semi-quantitative measure such as a relative rates, ratios, grayscale images, or qualitative data based on an investigator-defined lexicon using descriptors such as weak, severe, mild, subtle, among others to describe an experimental outcome. AN important problem we've discovered is that engineering students do not identify or appropriately utilize biological data in problem solving and engineering design. Dr. Umulis' objective is to develop methods to increase student conceptual understanding of biological data so that they can effectively utilize biological data in engineering design and problem solving.
Systems analysis of BMP pattern formation in zebrafish. Dr. Umulis' group is collaborating closely with Dr. Mary Mullins' Lab at the University of Pennsylvania to discover mechanisms of BMP regulation in zebrafish by utilizing quantitative image acquisition and analysis, mathematical models of early zebrafish embryo DV patterning, and mixed-quality constraint based optimization. We are aiming to develop, optimize, and analyze 3D spatiotemporal models of BMP patterning in zebrafish to elucidate the complex spatiotemporal regulation of BMP signaling.