@inbook{16994ba21e1648fdb6bed0d14a24937e,
title = "Empirical study of computational intelligence strategies for biochemical systems modelling",
abstract = "Modelling biochemical networks can be achieved by iteratively analyzing parts of the systems via top-down or bottom-up approaches. It is feasible to piece-wise model the biochemical networks from scratch by employing strategies able to assemble reusable components. In this paper, we investigate a set of strategies that can be employed in a bottom-up piece-wise modelling framework, to obtain synthetic models with similar behaviour to the target systems. A combination of evolution strategies and simulated annealing is employed to optimize the structure of the system and its kinetic rates. Simulation results of different variants of those computational methods on a standard signaling pathway show that it is feasible to obtain a tradeoff between the generation of desired behaviour and similar and alternative topologies.",
author = "Zujian Wu and Crina Grosan and David Gilbert",
year = "2014",
doi = "10.1007/978-3-319-01692-4_19",
language = "English",
isbn = "9783319016917",
series = "Studies in Computational Intelligence",
publisher = "Springer Verlag",
pages = "245--260",
booktitle = "Nature Inspired Cooperative Strategies for Optimization (NICSO 2013)",
address = "Germany",
}