证候具有“动态时空”属性，其宏观的动态改变必然有微观组学网络系统与之相对应。然而目前这种对应关系的研究多为对横断面的静态定性分析，尚未开展证候与其对应基因网络的动态关联定量分析。本研究在前期建立的血瘀证证候动态变化的时效定量模型基础上，依托丹红注射液治疗急性脑梗死血瘀证3个时间点的mRNA组学数据（0天，第14天，第90天），构建急性脑梗死血瘀证差异基因共表达动态网络，采用动态频繁子图法挖掘基因共表达动态网络的核心动态模块，然后采用偏最小二乘差异网络分析法结合前期血瘀证证候时效动力学模型，建立急性脑梗死血瘀证与基因共表达网络核心动态模块的定量关联，通过GO功能富集和KEGG通路富集分析核心动态模块，揭示证候动态变化的转录调控机制，从而从微观层面诠释证候随时间改变的动态属性特征。

Zhenghou has temporal-spatial dynamic property，which macroscopic dynamic change should be associated with the corresponding microscopic transcriptomic network system. However, recent studies on this relationship mostly were the static cross-section analysis, rather than the quantitative analysis of dynamic association. Previously, We had established a T-pharmacodynamics model of Xueyu Zheng. This study continue to construct a quantitative dynamic model on the relationship between the acute cerebral infarction (Xueyu Zheng) and the dynamic differential gene co-expression network based on the data from an ongoing trial on Danhong injection for the treatment of acute cerebral infarction (Xueyu Zheng). Firstly, using the temporal data of mRNA omics data on Day 0,Day 14 and Day 90, we will build a dynamic gene co-expression network of acute cerebral infarction (Xueyu Zheng), and obtain the core dynamic module using the analysis of dynamic frequent subgraph. Secondly, we will establish the quantitative correlation model between the symptoms Score of acute cerebral infarction (Xueyu Zheng) and the gene expression of the core dynamic module based on the previous T-pharmacodynamics model of Xueyu Zheng using the differential network analysis of the partial least squares (PLS)regression. Finally, we will analysis the molecular function of the core dynamic module through GO and KEGG enrichment anlysis to reveal the molecular mechanism of transcription regulation for the dynamic property of acute cerebral infarction (Xueyu Zheng). Our study will provide a method on the annotation for the dynamic property of Zhenghou.