Abstract
Eisen’s tree view is a useful tool for clustering and displaying of microarray gene expression data. In Eisen’s tree view system, a hierarchical method is used for clustering data. However, some useful information in gene expression data may not be well drawn when a hierarchical clustering is directly used in Eisen’s tree view. In this paper, we embed the similarity-based clustering method (SCM) into the tree view system so that microarray data can be re-organized according to the structure of data. The created SCM-driven tree view can give a better dendrogram display for microarray gene expression data with more useful information.
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Kuo, HC., Yang, MS., Yang, JH., Chen, YC. (2014). SCM-driven Tree View for Microarray Data. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_19
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DOI: https://doi.org/10.1007/978-3-319-07176-3_19
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07175-6
Online ISBN: 978-3-319-07176-3
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