Modeling genetic networks: Comparison of static and dynamic models

C. Rubio-Escudero, R. Romero-Záliz, O. Cordón, I. Zwir

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Biomedical research has been revolutionized by highthroughput 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.

Original languageEnglish
Title of host publicationSummer Computer Simulation Conference 2007, SCSC'07, Part of the 2007 Summer Simulation Multiconference, SummerSim'07
Pages827-832
Number of pages6
StatePublished - 2007
EventSummer Computer Simulation Conference 2007, SCSC 2007, Part of the 2007 Summer Simulation Multiconference, SummerSim 2007 - San Diego, CA, United States
Duration: Jul 15 2007Jul 18 2007

Publication series

NameSummer Computer Simulation Conference 2007, SCSC'07, Part of the 2007 Summer Simulation Multiconference, SummerSim'07
Volume2

Conference

ConferenceSummer Computer Simulation Conference 2007, SCSC 2007, Part of the 2007 Summer Simulation Multiconference, SummerSim 2007
Country/TerritoryUnited States
CitySan Diego, CA
Period07/15/0707/18/07

Keywords

  • Dynamic models
  • Gene networks
  • High-throughput techniques
  • T gene expression

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