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EMILiO: A fast algorithm for genome-scale strain design

Paper ID Volume ID Publish Year Pages File Format Full-Text
31670 44828 2011 10 PDF Available
Title
EMILiO: A fast algorithm for genome-scale strain design
Abstract

Systems-level design of cell metabolism is becoming increasingly important for renewable production of fuels, chemicals, and drugs. Computational models are improving in the accuracy and scope of predictions, but are also growing in complexity. Consequently, efficient and scalable algorithms are increasingly important for strain design. Previous algorithms helped to consolidate the utility of computational modeling in this field. To meet intensifying demands for high-performance strains, both the number and variety of genetic manipulations involved in strain construction are increasing. Existing algorithms have experienced combinatorial increases in computational complexity when applied toward the design of such complex strains. Here, we present EMILiO, a new algorithm that increases the scope of strain design to include reactions with individually optimized fluxes. Unlike existing approaches that would experience an explosion in complexity to solve this problem, we efficiently generated numerous alternate strain designs producing succinate, l-glutamate and l-serine. This was enabled by successive linear programming, a technique new to the area of computational strain design.

Keywords
Strain design; Optimization; Successive linear programming; Succinate; Amino acid
First Page Preview
EMILiO: A fast algorithm for genome-scale strain design
Publisher
Database: Elsevier - ScienceDirect
Journal: Metabolic Engineering - Volume 13, Issue 3, May 2011, Pages 272–281
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering