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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Advisor: Eberhard O. Voit, Ph.D.
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology
Committee Members:
Andreas S. Bommarius, Ph.D.
School of Chemical and Biomolecular Engineering, Georgia Institute of Technology
Michael J. Leamy, Ph.D.
The George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology
Pamela Peralta-Yahya, Ph.D.
School of Chemical and Biomolecular Engineering, Georgia Institute of Technology
Peng Qiu, Ph.D.
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology
Title: Computational Inference of the Structure and Regulation of the Lignin Pathway in Panicum virgatum
Abstract: Switchgrass is a prime target for biofuel production from inedible plant parts and has been the subject of numerous investigations in recent years. Yet, one of the main obstacles to effective biofuel production remains to be the major problem of recalcitrance. Recalcitrance emerges in part from the 3-D structure of lignin as a polymer in the secondary cell wall. Lignin limits accessibility of the sugars in the cellulose and hemicellulose polymers to enzymes and ultimately decreases ethanol yield. Monolignols, the building blocks of lignin polymers, are synthesized in the cytosol and translocated to the plant cell wall, where they undergo polymerization. The biosynthetic pathway leading to monolignols in switchgrass is not completely known, and difficulties associated with in vivo measurements of these intermediates pose a challenge for a true understanding of the functioning of the pathway. The proposed work aims to apply a systems biological modeling approach to address this challenge.
