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

Frontiers of Computer Science 2013年第2期7卷 204-213页

作者： R PRISCILLA S SWAMYNATHAN Department of Information and Science and Technology The College of Engineering Guindy Campus Anna UniversityIndia Chennai 600025

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.

关键词： clustering hierarchical clustering supervisedclustering overlapping clustering

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