A semi-supervised hierarchical approach： two-dimensional clustering of microarray gene expression data

作     者：R PRISCILLA S SWAMYNATHAN 

作者机构：Department of Information and Science and Technology The College of Engineering Guindy Campus Anna UniversityIndia Chennai 600025 

出 版 物：《Frontiers of Computer Science》 (中国计算机科学前沿（英文版）)

年 卷 期：2013年第7卷第2期

页      面：204-213页

核心收录：

学科分类：0710[理学-生物学] 0810[工学-信息与通信工程] 0808[工学-电气工程] 07[理学] 08[工学] 09[农学] 081002[工学-信号与信息处理] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：clustering hierarchical clustering supervisedclustering overlapping clustering 

摘      要：Micro array technologies have become a widespread research technique for biomedical researchers to assess tens of thousands of gene expression values simul- taneously in a single experiment. Micro array data analysis for biological discovery requires computational tools. In this research a novel two-dimensional hierarchical clustering is presented. From the review, it is evident that the previous research works have used clustering which have been ap- plied in gene expression data to create only one cluster for a gene that leads to biological complexity. This is mainly because of the nature of proteins and their interactions. Since proteins normally interact with different groups of proteins in Order to serve different biological roles, the genes that produce these proteins are therefore expected to co express with more than one group of genes. This constructs that in micro array gene expression data, a gene may makes its pres- ence in more than one cluster. In this research, multi-level micro array clustering, performed in two dimensions by the proposed two-dimensional hierarchical clustering technique can be used to represent the existence of genes in one or more clusters consistent with the nature of the gene and its attributes and prevent biological complexities.