Department of Biology, Colgate University, Hamilton, NY, USA.
Crit Rev Biochem Mol Biol. 2011 Apr;46(2):137-51. doi: 10.3109/10409238.2011.556597.
The detailed analysis of transcriptional networks holds a key for understanding central biological processes, and interest in this field has exploded due to new large-scale data acquisition techniques. Mathematical modeling can provide essential insights, but the diversity of modeling approaches can be a daunting prospect to investigators new to this area. For those interested in beginning a transcriptional mathematical modeling project, we provide here an overview of major types of models and their applications to transcriptional networks. In this discussion of recent literature on thermodynamic, Boolean, and differential equation models, we focus on considerations critical for choosing and validating a modeling approach that will be useful for quantitative understanding of biological systems.
转录网络的详细分析是理解核心生物过程的关键，由于新的大规模数据采集技术的出现，人们对这一领域的兴趣大增。数学建模可以提供重要的见解，但对于刚涉足该领域的研究人员来说，建模方法的多样性可能令人生畏。对于那些有兴趣开始转录数学建模项目的人，我们在此提供主要类型的模型及其在转录网络中的应用的概述。在讨论热力学、布尔和微分方程模型的最新文献时，我们重点讨论了对选择和验证建模方法至关重要的考虑因素，这些方法对于定量理解生物系统将是有用的。
