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Discovering Gene Clusters via Integrated Analysis on Time-Series and Group-Comparative Microarray Datasets

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3 Author(s)
V. S. Tseng ; National Cheng Kung University, Taiwan, R.O.C. ; Lien-Chin Chen ; Yao-Dung Hsieh

In this paper, we propose a novel gene clustering method named TGmix through integrated analysis on two types of datasets, namely the time-series and two-group microarray datasets. The goal of the proposed method is to discover genes as biomarkers that have similar expression profiles in time-series conditions and are also significantly differentially expressed in two-group conditions. We applied the proposed method to microarray datasets for rat's wound healing experiment, and the genes discovered in the same cluster conform to the analysis goal with related biological functions

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19th IEEE Symposium on Computer-Based Medical Systems (CBMS'06)

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