@inproceedings{c7bc7e50bd8d476092a421fb7fbef1d5,
title = "Optimal selection of enzyme levels using large-scale kinetic models",
abstract = "A hybrid optimization framework is introduced to identify enzyme sets and levels to meet overproduction requirements using kinetic models of metabolism. A simulated annealing algorithm is employed to navigate through the discrete space of enzyme sets while a sequential quadratic programming method is utilized to identify optimal enzyme levels. The framework is demonstrated on a model of E.coli central metabolism for serine biosynthesis. Computational results show that by optimally manipulating relatively small enzyme sets, a substantial increase in serine production can be achieved. The proposed approach thus provides a versatile tool for the elucidation of controlling enzymes with implications in biotechnology.",
author = "Nikolaev, {Evgeni V.} and Priti Pharkya and Maranas, {Costas D.} and Antonios Armaou",
note = "Funding Information: Financial support from the Pennsylvania State University, Dean{\textquoteright}s Fund, the NSF Award BES0120277, and the U.S. DOE is gratefully acknowledged. The authors are very grateful to Profs. Reuss and Schmid for providing us with the detailed kinetic model, and also would like to thank Dr. Burgard for helpful discussions and suggestions.",
year = "2005",
doi = "10.3182/20050703-6-cz-1902.02208",
language = "English (US)",
isbn = "008045108X",
series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",
publisher = "IFAC Secretariat",
pages = "25--30",
booktitle = "Proceedings of the 16th IFAC World Congress, IFAC 2005",
address = "Austria",
}