Modeling Gene Regulation Networks Using Ordinary Differential Equations

Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 802)

Abstract

Gene regulation networks are composed of transcription factors, their interactions, and targets. It is of great interest to reconstruct and study these regulatory networks from genomics data. Ordinary differential equations (ODEs) are popular tools to model the dynamic system of gene regulation networks. Although the form of ODEs is often provided based on expert knowledge, the values for ODE parameters are seldom known. It is a challenging problem to infer ODE parameters from gene expression data, because the ODEs do not have analytic solutions and the time-course gene expression data are usually sparse and associated with large noise. In this chapter, we review how the generalized profiling method can be applied to obtain estimates for ODE parameters from the time-course gene expression data. We also summarize the consistency and asymptotic normality results for the generalized profiling estimates.

Key words

Dynamic system Gene regulation network Generalized profiling method Spline smoothing Systems biology Time-course gene expression 

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Statistics and Actuarial ScienceSimon Fraser UniversityBurnabyCanada
  2. 2.School of Public HealthYale UniversityNew HavenUSA

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