May 2003
Volume 44, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2003
Networks of Gene Regulation Determined by mRNA Levels Measured by cDNA Microarrrays
Author Affiliations & Notes
  • L.S. Liebovitch
    Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, FL, United States
  • L.A. Shehadeh
    Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, FL, United States
  • V.K. Jirsa
    Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, FL, United States
  • Footnotes
    Commercial Relationships  L.S. Liebovitch, Florida Atlantic University P; L.A. Shehadeh, Florida Atlantic University P; V.K. Jirsa, Florida Atlantic University P.
Investigative Ophthalmology & Visual Science May 2003, Vol.44, 1293. doi:
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      L.S. Liebovitch, L.A. Shehadeh, V.K. Jirsa; Networks of Gene Regulation Determined by mRNA Levels Measured by cDNA Microarrrays . Invest. Ophthalmol. Vis. Sci. 2003;44(13):1293.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Abstract: : Purpose: To determine the overall pattern of how genes regulate other genes without first needing to discover the specific role of individual genes. Methods: We formulated different models of genetic regulatory networks, including random and "small world" models. We iterated these models until the mRNA levels reached a steady state. We then compared the probability density function, PDF(x), the number of genes expressing amounts of mRNA between x and x+dx, of the mRNA for the models and for the cDNA microarray data. Results: Different patterns of genetic regulatory networks produced different PDFs of mRNA levels. The experimental data is most like a model where different genes have different inputs from other genes, but similar outputs to other genes. Conclusions: We can identify different patterns of genetic regulatory networks. This may make it possible to identify the basic science systems that are most likely to be productive for further study and the clinical systems that are the best candidates for therapeutic intervention.

Keywords: gene microarray • gene/expression • transcription factors 
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