Jason A. Papin, PhD
Graduate School: University of California, San Diego
Primary Appointment: Assistant Professor, Biomedical Engineering
Systems biology, infectious disease, cancer
Email Address: firstname.lastname@example.org
Systems analysis has become a requirement for making sense of high-throughput data and for characterizing properties of biological networks. In order to extend these recent developments to medical applications, there is a pressing need for reconstructing and analyzing the signaling networks that direct cellular processes. Basically, we need to quantify how cells communicate with each other, a critical component of many human health problems as diverse as cancer and infectious disease.
In short, our research goal is the stoichiometric reconstruction and analysis of large-scale signaling networks and their application to human disease. Two primary questions drive our research: (1) How do network properties of a single cell emerge from the collection of components and interactions, and (2) How does a single cell function in its multi-cellular context?
Specifically, we have on-going projects in the following areas:
Intracellular signaling networks.
We are reconstructing the genome-scale cellular signaling networks of Saccharomyces cerevisiae and the human B-cell and macrophage. These reconstructions are critical for our efforts to integrate high-throughput data like protein-protein interaction maps and gene expression arrays into a cohesive and quantifiable framework. Diseases of particular interest include B-cell lymphomas.
Cell-cell signaling systems.
We are interested in how cellular signaling networks interact with each other to in multi-cellular systems. In collaborative work with several colleagues, we are reconstructing the signaling network critical for vulval development in Caenorhabditis elegans, and developing computational frameworks for analyzing multi-scale signaling processes (from cell to tissue-level characterizations). These projects are critical for tissue engineering applications and understanding cancer and developmental disorders.
We are reconstructing the metabolic and signaling networks for human pathogens involved in polymicrobial disease processes, including Candida albicans. This work addresses the challenges of how to account for multiple interacting microbial species, similar to the challenge of accounting for multiple interacting cells in a multi-cellular organism described above. Furthermore, we are interested in public health challenges as it relates to improving drug treatment of infectious disease for these organisms.
Tools for network analysis
Associated with the biological and medical application of the three research aims above, we develop methods for quantifying cellular network properties. We are developing approaches to: integrate signaling, metabolic, and regulatory networks; generate stoichiometric reconstructions from high-throughput data particular to signaling networks; and analyze dynamic properties of genome-scale signaling systems.
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