We are interested in relating molecular events to their physiological significance. To this end, we employ current system-wide, high throughput data acquisition approaches along with computational analysis. We use genome-scale data sets to construct computational system models of regulatory networks in mammalian cells. The following is a synopsis of current projects in the institute. These projects comprise experimental, computational and informatics domains to varying extents.
We integrate system-wide information from different data sources including gene and microRNA expression, transcription factor activity, genome-wide location analysis, cytokine profiles, and single cell data sets, to develop computational models of intracellular regulatory networks, cell-cell interactions, and organ physiology. We also develop new analysis methods that provide novel insights into the underlying control principles and regulatory mechanisms of physiological behavior.
- Central autonomic regulatory networks driving the development and maintenance of hypertension
- Liver function, repair and regeneration altered by adaptation to alcohol consumption
- Genomic studies of toxicological insult and brain development
- Effects of alcohol on brain systems involved with addictive and withdrawal processes
- Intracellular processes induced by growth factor signaling
Daniel Baugh Institute
- Computational modeling analysis of mitochondrial superoxide production under varying substrate conditions and upon inhibition of different segments of the electron transport chain
- Silence on the relevant literature and errors in implementation
- Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology
- Adiponectin fine-tuning of liver regeneration dynamics revealed through cellular network modelling
- Identifying functional gene regulatory network phenotypes underlying single cell transcriptional variability