Parameter estimation of S-systems using simulated annealing - Gonzalez, Orland Anthony Roxas (2004)
Modern technologies now allow the gathering of biological data at unprecedented levels. Specifically, temporal profiles of metabolites in biochemical systems are continuously being produced. These profiles are significant on that they contain biological information however will require systematic application of both experimental and computational methods. S-systems are non-linear mathematical models based on the power-law formalism. They provide a framework effective in dealing with integrated systems, a fact attested to by a history of successful applications. This research demonstrates the usefulness of an optimization technique called Simulated Annealing for the estimation of parameters of S-systems . We show how the technique alleviates some of the local minima problems that often plague other conventional algorithms by virtue of its ability to probabilistically escape from getting stuck. The technique's usefulness is demonstrated in 3 strategies. The first strategy involves traditional curve fitting using solutions to ODEs. This strategy is illustrated through a successful estimation of the parameters of a theoretical system with 4 dependent constituents. The second strategy exhibits how simulated annealing can be used in conjunction with methods of decoupling systems of ODE's. The power of this strategy is illustrated a comparison with the first strategy in estimating the parameters of the same theoretical system mentioned aove. Experimental results show dramatic reductions in running times. Finally, the third strategy demonstrates Simulated Annealing's usefulness in removing the bias introduced by decoupling. This is done through an application of the technique in a constrained local optimization using a theoretical system with 5 dependent and 3 independent constituents.
Thesis (M.S. Computer Science )--University of the Philippines Diliman.
Keywords: Nonlinear programming; Simulated annealing; Parameter estimation