Regulatory network of Escherichia coli:: Consistency between literature knowledge and microarray profiles
Regulatory network of Escherichia coli:: Consistency between literature knowledge and microarray profiles
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DOI：
10.1101/gr.1387003
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发表时间：
2003-11-01
期刊：
影响因子：
7
通讯作者：
Collado-Vides, J
中科院分区：
文献类型：
--
作者：
Gutiérrez-Ríos, RM;Rosenblueth, DA;Collado-Vides, J
大肠杆菌的转录网络很可能是单细胞中最完整的实验表征网络。建立了一种基于规则的方法来评估不同实验条件下的全基因组微阵列实验与大肠杆菌转录调控和操纵子组织数据库RegulonDB中积累的文献知识之间的一致性程度。我们观察到高度和统计显著的一致性水平，范围为70%-87%。当在预测调节蛋白的活性或非活性状态时不考虑调节蛋白的效应代谢物时，一致性下降了40%。类似地，当多个监管相互作用的规则被改变或“开”和“关”条目被随机分配时，一致性会降低。我们修改了调节器的初始状态，并评估了与调节器的连通性不线性相关的网络中误差的传播。我们将这种偏差主要解释为冗余监管相互作用存在的结果。一致性评估为理论与实验之间的对话开辟了一个新的空间，因为不同假设的结果可以被评估和比较。
The transcriptional network of Escherichia coli may well be the most complete experimentally characterized network of a single cell. A rule-based approach was built to assess the degree of consistency between whole-genome microarray experiments in different experimental conditions and the accumulated knowledge in the literature compiled in RegulonDB, a data base of transcriptional regulation and operon organization in E coli. We observed a high and statistical significant level of consistency, ranging from 70%-87%. When effector metabolites of regulatory proteins are not considered in the prediction of the active or inactive state of the regulators, consistency falls by LIP to 40%. Similarly, consistency decreases when rules for multiple regulatory interactions are altered or when "on" and "off" entries were assigned randomly. We modified the initial state of regulators and evaluated the propagation of errors in the network that do not correlate linearly with the connectivity of regulators. We interpret this deviation mainly as a result of the existence of redundant regulatory interactions. Consistency evaluation opens a new space of dialogue between theory and experiment, as the consequences of different assumptions can be evaluated and compared.