Title :
A new distance measurement for clustering time-course gene expression data
Author :
Chen, Guanrao ; Dai, Yang
Author_Institution :
Dept. of Comput. Sci., Illinois Univ., Chicago, IL, USA
Abstract :
The purpose of this paper is two-fold. First, a new distance measurement is proposed for temporal microarray gene expression data based on the angles of line segments in the curve of each individual gene expression profile. The hierarchical agglomerative clustering methods are used to incorporate this distance definition. Second, the assessment of the quality of clusterings obtained from the methods are provided by the use of the Davies-Bouldin validity index (DBI). We conclude that the DBI may not be an appropriate indicator for the quality assessment of clusters for time-course gene expression data. We provide an alternative DBI based on the normalized Pearson correlation for this purpose.
Keywords :
biology computing; cellular biophysics; distance measurement; genetics; molecular biophysics; pattern clustering; statistical analysis; Davies-Bouldin validity index; distance measurement; hierarchical agglomerative clustering methods; normalized Pearson correlation; temporal microarray gene expression data; time-course gene expression data; Bioinformatics; Clustering algorithms; Clustering methods; Distance measurement; Euclidean distance; Gene expression; Genomics; Noise measurement; Spline; Time measurement;
Conference_Titel :
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-8439-3
DOI :
10.1109/IEMBS.2004.1403832