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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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Mojdeh Faraji
BioE Ph.D. Defense Presentation
Date & Time: Tuesday, March 13, 2018, 1:00 pm
Location: room 3029, EBB
Advisor: Eberhard O. Voit, Ph.D. (Georgia Institute of Technology)
Committee:
Andreas Bommarius, Ph.D. (Georgia Institute of Technology)
Michael Leamy, Ph.D. (Georgia Institute of Technology)
Pamela Peralta-Yahya, Ph.D. (Georgia Institute of Technology)
Peng Qiu, Ph.D. (Georgia Institute of Technology)
From Experimental Observations to a Functional Model of the Lignin Pathway: Computational Modeling Reveals New Insights.
Lignin is a natural polymer that is interwoven with cellulose and hemicellulose within plant cell walls. Due to this molecular arrangement, lignin is a major contributor to the recalcitrance of plant materials with respect to the extraction of sugars and their fermentation into ethanol, butanol, and other potential bioenergy crops. The lignin biosynthetic pathway is similar, but not identical in different plant species. It is in each case comprised of a moderate number of enzymatic steps, but its responses to manipulations, such as gene knock-downs, are complicated by the fact that several of the key enzymes are involved in several reaction steps. This feature poses a challenge to bioenergy production, as it renders it difficult to select the most promising combinations of genetic manipulations for the optimization of lignin composition and amount. Moreover, species specific regulatory features and distinct spatial and topological characteristics hinder accuracy of a unified lignin pathway model. In this dissertation a systems biology approach is used to address these challenges by means of computational modeling. Novel mathematical techniques are employed on different types of experimental data in situ, and shed light on complexities of lignin biosynthesis pathway. The developed methods are nevertheless general enough to be used in a wide range of metabolic modeling applications.
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