title: Improving metabolic flux estimation via evolutionary optimization for convex solution space.
abstract: BACKGROUND
  Flux estimation by using (13) C-labeling pattern information of metabolites is currently the only method that can give accurate, detailed quantification of all intracellular fluxes in the central metabolism of a microorganism. In essence, it corresponds to a constrained optimization problem which minimizes a weighted distance between measured and simulated results. Characteristics, such as existence of multiple local minima, non-linear and non-differentiable make this problem a special difficulty.
  
  
  RESULTS
  In the present work, we propose an evolutionary-based global optimization algorithm taking advantage of the convex feature of the problem's solution space. Based on the characteristics of convex spaces, specialized initial population and evolutionary operators are designed to solve (13)C-based metabolic flux estimation problem robustly and efficiently. The algorithm was applied to estimate the central metabolic fluxes in Escherichia coli and compared with conventional optimization technique. Experimental results illustrated that our algorithm is capable of achieving fast convergence to good near-optima and maintaining the robust nature of evolutionary algorithms at the same time.
  
  
  BACKGROUND
  Available from the authors upon request.
authors.affiliation: Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China.
authors.forename: Jiusheng
authors.initials: J
authors.lastname: Chen
authors.forename: Haoran
authors.initials: H
authors.lastname: Zheng
authors.forename: Haiyan
authors.initials: H
authors.lastname: Liu
authors.forename: Junqing
authors.initials: J
authors.lastname: Niu
authors.forename: Jianping
authors.initials: J
authors.lastname: Liu
authors.forename: Tie
authors.initials: T
authors.lastname: Shen
authors.forename: Bin
authors.initials: B
authors.lastname: Rui
authors.forename: Yunyu
authors.initials: Y
authors.lastname: Shi
mesh_terms: D000465:Algorithms; D002244:Carbon / Q000378:metabolism*; D003198:Computer Simulation; D004734:Energy Metabolism / Q000502:physiology; D004926:Escherichia coli / Q000378:metabolism*; D029968:Escherichia coli Proteins / Q000378:metabolism*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology*
chemical_list: D029968:Escherichia coli Proteins; D002244:Carbon