libSRES: a C library for stochastic ranking evolution strategy for parameter estimation.
CONCLUSIONS
Estimation of kinetic parameters in a biochemical pathway or network represents a common problem in systems studies of biological processes. We have implemented a C library, named libSRES, to facilitate a fast implementation of computer software for study of non-linear biochemical pathways. This library implements a (mu, lambda)-ES evolutionary optimization algorithm that uses stochastic ranking as the constraint handling technique. Considering the amount of computing time it might require to solve a parameter-estimation problem, an MPI version of libSRES is provided for parallel implementation, as well as a simple user interface. libSRES is freely available and could be used directly in any C program as a library function. We have extensively tested the performance of libSRES on various pathway parameter-estimation problems and found its performance to be satisfactory.


BACKGROUND
The source code (in C) is free for academic users at http://csbl.bmb.uga.edu/~jix/science/libSRES/
Ji
Xinglai
X
Computational Biology Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
Xu
Ying
Y
D000465:Algorithms; D001671:Biochemistry / Q000379:methods*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D015723:Gene Library; D007700:Kinetics; D008957:Models, Genetic; D011381:Programming Languages; D017422:Sequence Analysis, DNA; D012984:Software; D013269:Stochastic Processes; D013997:Time Factors