Modeling genetic networks: comparison of static and dynamic models

Authors:
C. Rubio-Escudero;R. Romero-Záliz;O. Cordón;I. Zwir
Affiliations:
European Center for Soft Computing, Mieres, Spain;European Center for Soft Computing, Mieres, Spain;European Center for Soft Computing, Mieres, Spain;European Center for Soft Computing, Mieres, Spain and Washington University School of Medicine, St. Louis, MO.
Venue:
Proceedings of the 2007 Summer Computer Simulation Conference
Year:
2007

Citing 3
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Abstract

Biomedical research has been revolutionized by high-throughput techniques and the enormous amount of biological data they are able to generate. Genetic networks arise as an essential task to mine these data since they explain the function of genes in terms of how they influence other genes. Many modeling approaches have been proposed for building genetic networks up. However, it is not clear what the advantages and disadvantages of each model are. There are several ways to discriminate network building models, being one of the most important whether the data being mined presents a static or dynamic fashion. In this work we compare static and dynamic models over a problem related to the inflammation and the host response to injury. We show how both models provide complementary information and cross-validate the obtained results.