Modeling genetic networks: Comparison of static and dynamic models

Cristina Rubio-Escudero, Oscar Harari, Oscar Cordón, Igor Zwir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Biomedical research has been revolutionized by high-throughput techniques and the enormous amount of biological data they are able to generate. The interest shown over network models and systems biology is rapidly raising. 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.

Original languageEnglish
Title of host publicationEvolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 5th European Conference, EvoBIO 2007, Proceedings
Pages78-89
Number of pages12
StatePublished - Dec 1 2007
Event5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007 - Valencia, Spain
Duration: Apr 11 2007Apr 13 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4447 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2007
CountrySpain
CityValencia
Period04/11/0704/13/07

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    Rubio-Escudero, C., Harari, O., Cordón, O., & Zwir, I. (2007). Modeling genetic networks: Comparison of static and dynamic models. In Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 5th European Conference, EvoBIO 2007, Proceedings (pp. 78-89). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4447 LNCS).