Department of Physics, University of Houston, Houston, Texas, USA.
Biophys J. 2011 Dec 7;101(11):2563-71. doi: 10.1016/j.bpj.2011.10.008.
Circadian rhythms are governed by a highly coupled, complex network of genes. Due to feedback within the network, any modification of the system's state requires coherent changes in several nodes. A model of the underlying network is necessary to compute these modifications. We use an effective modeling approach for this task. Rather than inferred biochemical interactions, our method utilizes microarray data from a group of mutants for its construction. With simulated data, we develop an effective model for a circadian network in a peripheral tissue, subject to driving by the suprachiasmatic nucleus, the mammalian pacemaker. The effective network can predict time-dependent gene expression levels in other mutants.
昼夜节律受高度耦合的复杂基因网络调控。由于网络内的反馈，系统状态的任何改变都需要几个节点的协调变化。计算这些改变需要有一个底层网络的模型。我们使用一种有效的建模方法来完成这个任务。与推断生化相互作用不同，我们的方法利用了一组突变体的微阵列数据来构建模型。通过模拟数据，我们为一个受哺乳动物起搏器视交叉上核驱动的外周组织中的生物钟网络构建了一个有效的模型。该有效网络可以预测其他突变体的时变基因表达水平。
