I have modeled a variety of biological systems, mainly using the algorithms that I have developed with collaborators.
A Computational Algebra Approach to the Reverse Engineering of Gene Regulatory Networks
R. Laubenbacher and I reverse engineered the segment polarity network in the fruit fly D. melanogaster and showed that our Boolean dynamical system model reproduced all experimentally observed steady states. Furthermore, the model identified two other biologically feasible steady states through analysis of the model. We were able to use the model to explain why certain interactions were unidentifiable given the observed data.
Boolean Models Can Explain Bistability in the lac Operon
A. Veliz-Cuba and I presented the first discrete model of the lac operon in E. coli to include all known glucose control mechanisms and to exhibit bistability, which has been observed experimentally. We also provided a novel method for reducing the size of the model without losing desired network features.
A Regulatory Network Modeled from Wild-type Gene Expression Data Guides Functional Predictions in Caenorhabditis elegans Development
H. Chamberlin and I reverse engineered the gene regulatory network responsible for mesoderm and ectoderm development in embryo of the nematode C. elegans. The model was shown to identify more experimentally-validated interactions than an existing model and provided novel hypotheses for the epithelial-mesenchymal transition which can be hijacked by certain epithelial cancers.
Reverse Engineering a Yeast Oxidative Stress Response Network
Collaborators and I reverse engineered the transcriptional oxidative stress response network in the yeast S. cerevisiae. We proposed a novel pathway involving one of the transcription factors in the network.