4.5 Article

TWO-LAYER MATHEMATICAL MODELING OF GENE EXPRESSION: INCORPORATING DNA-LEVEL INFORMATION AND SYSTEM DYNAMICS

期刊

SIAM JOURNAL ON APPLIED MATHEMATICS
卷 73, 期 2, 页码 804-826

出版社

SIAM PUBLICATIONS
DOI: 10.1137/120887588

关键词

reaction-diffusion equation; thermodynamic equilibrium; transcriptional regulation

资金

  1. NIH [GM056976]
  2. Teaching and Research Postdoctoral Fellowship at Harvey Mudd College
  3. NSF [DMS-0839966]
  4. Division Of Mathematical Sciences
  5. Direct For Mathematical & Physical Scien [0839966] Funding Source: National Science Foundation

向作者/读者索取更多资源

High-throughput genome sequencing and transcriptome analysis have provided researchers with a quantitative basis for detailed modeling of gene expression using a wide variety of mathematical models. Two of the most commonly employed approaches used to model eukaryotic gene regulation are systems of differential equations, which describe time-dependent interactions of gene networks, and thermodynamic equilibrium approaches that can explore DNA-level transcriptional regulation. To combine the strengths of these approaches, we have constructed a new two-layer mathematical model that provides a dynamical description of gene regulatory systems, using detailed DNA-based information, as well as spatial and temporal transcription factor concentration data. We also developed a semi-implicit numerical algorithm for solving the model equations and demonstrate here the efficiency of this algorithm through stability and convergence analyses. To test the model, we used it together with the semi-implicit algorithm to simulate a Drosophila gene regulatory circuit that drives development in the dorsal-ventral axis of the blastoderm-stage embryo, involving three genes. For model validation, we have done both mathematical and statistical comparisons between the experimental data and the model's simulated data. Where protein and cis-regulatory information is available, our two-layer model provides a method for recapitulating and predicting dynamic aspects of eukaryotic transcriptional systems that will greatly improve our understanding of gene regulation at a global level.

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