Identification of hair cycle-associated genes from time-course gene expression profile using fractal analysis
by Sunil K. Mathur, Atul M. Doke, Ajit Sadana
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 2, No. 3, 2006

Abstract: Microarray technology permits one to monitor thousands of processes going on inside the cell. This tool has been used to study gene expression profiles associated with the hair-growth cycle. We provide a novel method called the fractal analysis method to identify hair-growth cycle associated genes from time course gene expression profiles. Fractal analysis is a much better method than the computational method used by Lin et al. (2004). The fractal dimension obtained by fractal analysis process also indicates the irregularity in hair-growth pattern. The computational method used by Lin et al. (2004) was unable to make any inference about the hair-growth pattern.

Online publication date: Mon, 07-Aug-2006

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