Philadelphia University + Thomas Jefferson University

Research

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 whole genome and proteome data to construct computational system models of regulatory and enzymatic networks in mammalian cells.

The following is a synopsis of past and current projects in the institute. These projects comprise experimental, computational and informatic domains to varying extents.

Experimental Studies: We use in vivo and in vitro experiments to characterize physiological response to specific stimuli. We employ a pipeline of experimental methods to achieve high throughput in the creation and use of large, high-density protein, protein-state and gene expression microarrays.

  • Effects of alcohol on organ systems involved with addictive and withdrawal processes
    • brain systems
    • liver
  • Intracellular signaling processes induced by EGFR, e.g. in hepatocytes and alcohol treatment
  • Genomic and compuatational studies of toxicological insult and brain development
  • Effects of hypertension on gene expression in nucleus tractus solitaris (NTS)
  • Role of Regulator of G-protein Signalling proteins in neuronal function
  • Neuropeptide effects on gene expression in neurons
  • Information transfer and signal processing in the respiratory control system
  • Functional imaging of intact neural systems

Computational Analysis: We integrate system-wide information from different data sources to create comprehensive mathematical models of cellular function. We also develop innovative analysis methods that provide novel insights into the underlying mechanisms of physiological behavior.

  • CAKE – a framework for validation of genetic regulatory network identification methods
  • Methods for genetic regulatory network identification
    • Linear systems methods
    • Bayesian approach
  • Signal Transduction Networks
  • Multi-time scale analysis of complex adaptive systems

Bioinformatics Tools: The success of Experimental and Computational studies requires an efficient informatics platform that renders raw data amenable to further analysis. The key components of this platform are data storage, data mining, experiment tracking, and integration with external databases.