Session 66 - Advances in Metabolic Engineering and Bioinformatics II


Bioengineering
Session 66 - Advances in Metabolic Engineering and Bioinformatics II
Metabolic engineering is the targeted improvement of the cellular metabolic phenotype using recombinant DNA technology. Experimental and mathematical techniques that are used to characterize metabolic networks are also included. Bioinformatics tools are critical for the advancement of metabolic engineering and many other fields in biotechnology. Abstracts describing new developments in these topics are sought, and those incorporating both mathematical modeling and experimental aspects are particularly encouraged. Example areas include quantification of metabolic fluxes, inverse metabolic engineering, production of novel products, application of evolutionary techniques, construction of metabolic models from genomic data, incorporation of microarray and proteomic data and mathematical modeling of metabolism. The session is open to papers focused on any type of organism.
Chair:	Vassily Hatzimanikatis
CoChair:	Nathan D. Price
	66a	Biobutanol from Yeast. A Synergistic Genome and Protein Engineering Approach Nikhil U. Nair, Zengyi Shao, Hua Zhao, Ryan P. Sullivan, Michael McLachlan, Tyler W. Johannes, Huimin Zhao
	66b	Effects of Glucose and Insulin Levels on HepG2 Cell Metabolism Vidya V. Iyer, Charles M. Roth, M.G. Ierapetritou
	66c	Distilling the Complexity of Metabolic ChEmistry Christopher Henry, Linda J. Broadbelt, Vassily Hatzimanikatis
	66d	Coregulation Analysis of Highly Coexpressed and Non-Coexpressed Genes with a Novel Promoter Similarity Index Nguyen Tung, Richard Nowakowski, Ioannis P. Androulakis
		Break
	66e	Improving Cofactor Availability through Metabolic Engineering for Recombinant Phytochemicals Production Joseph ChEmler, Zachary Fowler, Mattheos Koffas
	66f	Identification of Optimal Measurement Sets for Isotopically Non-Stationary Mfa Experiments YoungJung Chang, Patrick F. Suthers, Costas D. Maranas
	66g	Determining Metabolic Fluxes Using Experimental Measurements Jennifer L. Reed, Qiang Hua, Bernhard O. Palsson

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