Carlos F. Lopez Ph. D.: My formal training has been in the fields of chemistry, physics, biophysics, biochemistry, and molecular cell biology with a unique emphasis on the development and application of modeling techniques. I recently started at Vanderbilt University School of Medicine to apply my knowledge in cell molecular and systems biology with a focus in cancer research. Given my training from atomic interactions to continuum-cellular interactions I am deeply interested in how events that take place at one space-time scale (e.g. quantum interactions) have an effect on the interactions at the macroscale. From this perspective, cancer biology is a perfect area of application to my theoretical interests due to its inherent multi-scale properties. At the same time, I believe a thorough understanding of cancer development and progression necessitates the development of a multi-scale theoretical foundation that can account for events such as DNA/genomic level aberrations (atomic space and time scales), protein malfunctions, and others, and their propagation to proteins (molecular scales), organelles, cells, and ultimately organs. My driving hypothesis is that understanding the events involved in cancer at multiple scales and developing theories and models to explore cancer biology from systems perspective are key to developing novel successful cancer treatments. This goal is quite ambitious, and I am approaching it by initially focusing on cell signaling pathways that exhibit dysregulation in cancer phenotypes. I also work on trying to provide a novel theoretical understanding of cancer progression that, in turn, will open new possibilities for targeted treatments.
Erin Shockley, Graduate Student: I want to understand how cells choose between survival and death via apoptosis, in the context of cell signaling. Too much or too little apoptosis plays a role in many human diseases, including cancer, in which cells that should die for the good of the organism stubbornly live on, often in spite of targeted therapies designed to destroy them. Understanding how cells resist targeted therapies requires understanding the large signaling networks these therapies are designed to perturb, and how those networks integrate with the intrinsic apoptosis pathway. Computational modeling of these signaling networks provides a tool to study these extremely complex, intertwined systems. In order to study the cellular decision between survival and apoptosis in a system that is complex and interconnected, but not intractably large, I model signaling in cancer cells dependent upon ErbB signaling through the MAPK and PI3K pathways for survival. I intend to develop a model predictive of apoptosis in response to different targeted therapies, which will allow me to understand what signaling nodes are key in mediating the apoptotic response and will suggest how the signaling network rebalances in order to develop therapeutic resistance.
Michael Irvin, Graduate Student: Apoptosis/Necrosis cell processes.
Michael Kochen, Graduate Student: Logic models.
James Pino, Graduate Student: Big data to big mechanism. Stochastic modeling of cell decisions through creation of simulation tools and analysis methods. Molecular simulation of pore formation of the mitochondria in apoptosis.
Oscar Ortega, Graduate Student: Dynamics of signaling networks.
Leonard Harris, Postdoctoral Fellow: Cell population dynamics.
Alexander Lubbock, Postdoctoral Fellow: Modeling infrastructure and stochastic cellular systems.