Parameter estimation for biochemical model systems has become an important problem in systems biology. Here we focus on the metabolic subnetwork of the valine and leucine biosynthesis in C. glutamicum. Due to the lack of indisputable information regarding reversibility of the reactions in the pathway we derived two alternative ordinary differential equation models based on the formalisms of the generalized mass-action rate law. We introduced two alternative modeling approaches for feedback inhibition and evaluated the applicability of six optimization procedures (multi start Hill Climber, binary and real valued Genetic Algorithm, standard and covariance matrix adaption Evolution Strategy as well as Simulated Annealing) to the problem of parameter fitting. The model considering irreversible reactions performed worse and was therefore rejected from further analysis. We benchmarked the impact of different mutation and crossover operators as well as the influence of the population size on the remaining system and the two best optimization procedures namely binary Genetic Algorithm and the Evolution Strategy. The GA performed best on average and found the best total result based on the relative squared error.
@inproceedings{Draeger2007a,
author = {Dr\"ager, Andreas and Supper, Jochen and Planatscher, Hannes and
Magnus, J{\o}rgen B. and Oldiges, Marco and Zell, Andreas},
title = {{Comparing Various Evolutionary Algorithms on the Parameter Optimization
of the Valine and Leucine Biosynthesis in \emph{Corynebacterium glutamicum}}},
booktitle = {IEEE Congress on Evolutionary Computation (CEC 2007)},
year = {2007},
editor = {Srinivasan, Dipti and Wang, Lipo},
pages = {620--627},
address = {Singapore},
month = sep,
organization = {IEEE Computational Intelligence Society},
publisher = {IEEE Press},
abstract = {Parameter estimation for biochemical model systems has become an important
problem in systems biology. Here we focus on the metabolic subnetwork
of the valine and leucine biosynthesis in \emph{C.~glutamicum}. Due
to the lack of indisputable information regarding reversibility of
the reactions in the pathway we derived two alternative ordinary
differential equation models based on the formalisms of the generalized
mass-action rate law. We introduced two alternative modeling approaches
for feedback inhibition and evaluated the applicability of six optimization
procedures (multi start Hill Climber, binary and real valued Genetic
Algorithm, standard and covariance matrix adaption Evolution Strategy
as well as Simulated Annealing) to the problem of parameter fitting.
The model considering irreversible reactions performed worse and
was therefore rejected from further analysis. We benchmarked the
impact of different mutation and crossover operators as well as the
influence of the population size on the remaining system and the
two best optimization procedures namely binary Genetic Algorithm
and the Evolution Strategy. The GA performed best on average and
found the best total result based on the relative squared error.},
doi = {10.1109/CEC.2007.4424528},
isbn = {1-4244-1340-0},
keywords = {systems biology, mathematical modeling, benchmark, Evolutionary Algorithms,
valine and leucine biosynthesis, Corynebacterium glutamicum, generalized
mass-action kinetics},
notes = {CEC 2007 - A joint meeting of the IEEE, the EPS, and the IET, Dr\"ager,
Andreas and Supper, Jochen and Planatscher, Hannes and Magnus, J{\o}rgen
B. and Oldiges, Marco and Zell, Andreas IEEE Catalog Number: 07TH8963C},
pdf = {http://www.cogsys.cs.uni-tuebingen.de/publikationen/2007/Draeger2007a.pdf},
url = {http://dx.doi.org/10.1109/CEC.2007.4424528}
}