May 29, 2000

Modeling transcriptional control in gene networks--methods, recent results, and future directions

Bulletin of Mathematical Biology
P SmolenJ H Byrne


Mathematical models are useful for providing a framework for integrating data and gaining insights into the static and dynamic behavior of complex biological systems such as networks of interacting genes. We review the dynamic behaviors expected from model gene networks incorporating common biochemical motifs, and we compare current methods for modeling genetic networks. A common modeling technique, based on simply modeling genes as ON-OFF switches, is readily implemented and allows rapid numerical simulations. However, this method may predict dynamic solutions that do not correspond to those seen when systems are modeled with a more detailed method using ordinary differential equations. Until now, the majority of gene network modeling studies have focused on determining the types of dynamics that can be generated by common biochemical motifs such as feedback loops or protein oligomerization. For example, these elements can generate multiple stable states for gene product concentrations, state-dependent responses to stimuli, circadian rhythms and other oscillations, and optimal stimulus frequencies for maximal transcription. In the future, as new experimental techniques increase the ease of characterization of genetic networks,...Continue Reading

  • References83
  • Citations106


  • References83
  • Citations106


Mentioned in this Paper

Stochastic Processes
Transcriptional Regulation
Alkalescens-Dispar Group
Transcription, Genetic
Feedback - System Communication
Protein Oligomerization
Genome Encoded Entity
Circadian Rhythm Pathway 2
Gene Regulatory Networks

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