时序微阵列数据中的同步和异步共调控基因聚类

Mining Synchronous and Asynchronous Co-Regulated Gene Clusters from Time Series Microarray Data

基因的共调控可分为同步和异步两种.文中提出了一种新的聚类模型Reg-Cluster,将具有相同编码的同步和异步共调控基因聚集到同一个共调控基因类中.在此基础上,提出了一种有效的聚类算法FBLD,采用先宽度优先、后深度优先的搜索策略,并结合高效的削减规则,挖掘得到所有符合条件的最大Reg-Cluster.聚类结果中包含了详细而完备的共调控信息,有助于基因调控网的研究.算法可扩展用于三维基因-样本-时间微阵列数据集的分析.FBLD算法已经应用到真实和人造微阵列数据集中,其结果被提交到Gene Ontology,实验结果证明了算法的高效性和有效性.

Gene co-regulation falls into two major categories, i.e. synchronous and asynchoronous co-regulation. This paper proposes a new model Reg-Cluster, which groups synchronous and asynchoronous co-regulated genes together if they have the same code. Further, an effective clustering algorithm with several efficient pruning rules, namely FBLD, is designed to identify all maximal Reg-Clusters in a ＂First Breadth-first and Last Depth-first＂ manner. The resultant clusters contain the detailed and complete co-regulation information, which facilitates the study of genetic regulatory networks. Moreover, the method can be extended to the analysis of 3D genesample-time microarray data. The FBLD algorithm has been implemented on both real and synthetic datasets and the results from the real dataset has been submitted to Gene Ontology. Experimental results prove the effectiveness and efficiency of the proposed method.