We have developed an efficient algorithm base on the genetic algorithm
(GA) for optimization of a nonlinear system where the details of gene
regulatory networks.
Estimation of the interaction mechanisms among system components by
using experimentally observed dynamic responses (time-courses) of
some of the system components is generally referred to as "inverse
problem". The S-system, which belongs to power-law formalism,
is one of the best representations to solve such an inverse problem;
the S-system is rich enough in structure to capture all relevant dynamics.
In our research, for the purpose of solving the inverse problem, we
introduce the genetic algorithm and propose an efficient procedure
for the estimation of large number of parameters in the S-system formalism.
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1. Measure gene
expression levels with DNA microarray technology in time.
2. Our algorithm optimizes mathematical network models to fit
to observed expression data.
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| Relational Information |
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AIST Today Vol. 3, No. 3 (2003) 12
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No.8
Spring 2003
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