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• W1564992779 abstract "Abstract — Microarray experiments are information rich; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. For biologists, a key aim when analyzing microarray data is to group genes based on the temporal patterns of their expression levels. In this paper, we used an iterative clustering method to find temporal patterns of gene expression. We evaluated the performance of this method by applying it to real sporulation data and simulated data. The patterns obtained using the iterative clustering were found to be superior to those obtained using existing clustering algorithms. Keywords — Clustering, microarray experiment, temporal pattern of gene expression data . I. I NTRODUCTIONHE rapid development of microarray technologies has made it possible to monitor the expression levels of thousands of genes simultaneously [1]. These technologies have proved a boon in the biological and medical sciences, where they have assisted researchers in tackling such broad problems as tumor classification. Microarray experiments provide a wealth of information; however, extensive data mining is required to identify the patterns that characterize the underlying mechanisms of action. For biologists, a key aim when analyzing microarray data is to group genes based on the temporal patterns of their expression levels, which may provide insights into genetic capacities and their interactions. Indeed, microarray experiments in cellular contexts have shown that genes with similar functions often evince similar temporal patterns of co-regulation [2], [3]. Due to the large number of genes involved in these experiments and the complexity of biological processes in general, an effective clustering algorithm for grouping genes is crucial to such studies. Clustering analysis is faced with two problems: how to determine the number of true clusters and how to evaluate the" @default.
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• W1564992779 date "2005-01-01" @default.
• W1564992779 modified "2023-09-27" @default.
• W1564992779 title "Iterative Clustering Algorithm for Analyzing Temporal Patterns of Gene Expression." @default.
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