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Research

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My goal is to develop close collaborations with strong experimental and theoretical components. By blending cross and inter-disciplinary expertise we hope to expand scientific inquiry in new and exciting directions. General science write-ups on our research:

Current Research Support

  • NSF PHY 1205840, Damage mitigation in signal transduction networks (PI) NSF
  • MCB 1121612, MPS-BIO: Networks of Heterotrimeric Gα Subunit Signaling to K+ Channels in Arabidopsis Guard Cells (co-PI) NSF IIS 1161007, Collaborative
  • Research: Combinatorial Analysis of Biological and Social Networks (PI)

Research Group

  • Dr. Jorge G. T. Zanudo
  • Steven Steinway
  • Xiao Gan
  • Gang Yan

Group Alumni

Ph.D. Graduates (2003-2016)

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  1. Dr. Zhongyao Sun
  2. Dr. Ranran Zhang
  3. Dr. Usha Nandini Raghavan
  4. Dr. Claire Christensen
  5. Dr. Hari Thadakamalla
  6. Dr. Christopher Carrino
  7. Dr. Song Li
  8. Dr. Assieh Saadatpour

Postdoctoral Associates (2003-2016)

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  1. Dr. Jorge G. T. Zanudo
  2. Dr. Colin Campbell
  3. Dr. Anshuman Gupta
  4. Dr. Jaewook Joo
  5. Dr. Juilee Thakar
  6. Dr. Suann Yang
  7. Dr. Rui-Sheng Wang

Research Areas

Modeling epithelial to mesenchymal transition in liver cancer

Epithelial-to-mesenchymal transition (EMT) is a developmental process hijacked by cancer cells to leave the primary tumor site, invade surrounding tissue, and establish distant metastases. We have constructed an EMT network of 70 nodes and 135 edges by integrating the signaling pathways involved in developmental EMT and known dysregulations in invasive liver cancer. We then used discrete dynamic modeling to understand the dynamics of the EMT network driven by TGFβ. We used the model to identify combinatorial interventions for the suppression of EMT, and validated them by siRNA experiments. We also found that many apparently successful single interventions may lead to steady states that are in-between epithelial and mesenchymal states.

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Collaborators:

  • Thomas P. Loughran, M.D., University of Virginia School of Medicine

Modeling ecological communities

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Relationships such as those between predators and prey, or symbiotic interactions like those of plants and insect pollinators, link the species of an ecological community into a complex network of interdependence. This means that the demise of one species can have knock-on effects that are hard to predict and may occasionally be catastrophic.

Collaborators:

  • Prof. Katriona Shea, Professor of Biology, Penn State

Signal transduction in plant guard cells

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Plants have developed sophisticated signal transduction mechanisms to be able to respond to changing environmental conditions. One such mechanism is the opening of stomata (pores) to light and closing them in response to drought conditions. We have synthesized experimental information on light and drought signaling to reconstruct and model the signal transduction network of guard cells. Our work has identified knowledge gaps and has generated new predictions and hypotheses.

Collaborators:

  • Prof. Sarah Assmann, Waller Professor of Biology, Department of Biology, Penn State

Signaling Network Model of Cytotoxic T lymphocytes in T-LGL Leukemia

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Cytotoxic T lymphocytes (CTL) are a group of T cells that are essential for eliminating infected cells and tumor cells. T-cell large granular lymphocyte (T-LGL) leukemia features a clonal expansion of antigen-primed CTL that successfully escaped activation induced cell death (AICD), a process that normally occurs after CTL activation. This disease provides us a unique opportunity to decipher the key mediators of CTL activation and AICD in humans. We developed a model of the signaling network involved in maintaining long-term survival of competent CTL in humans. We used the model to identify potential therapeutic targets for T-LGL leukemia.

Collaborators:

  • Thomas P. Loughran, M.D., University of Virginia School of Medicine