Abstract
Systems biology is the ever-growing field of integrating molecular knowledge about biological organisms into an understanding at the systems level. For this endeavour, automatic network reconstruction tools are urgently needed. In the present contribution, we show how the applicability of evolutionary algorithms to systems biology can be improved by a domain-specific representation and algorithmic extensions, especially a separation of network structure evolution from evolution of kinetic parameters. In a case study, our presented tool is applied to a model of the mitotic spindle checkpoint in the human cell cycle. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Lenser, T., Hinze, T., Ibrahim, B., & Dittrich, P. (2007). Towards evolutionary network reconstruction tools for systems biology. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4447 LNCS, pp. 132–142). Springer Verlag. https://doi.org/10.1007/978-3-540-71783-6_13
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