Title: Identification of hair cycle-associated genes from time-course gene expression profile using fractal analysis
Authors: Sunil K. Mathur, Atul M. Doke, Ajit Sadana
Addresses: Department of Mathematics, University of Mississippi, MS 38677-1848, USA. ' Department of Chemical Engineering, University of Mississippi, MS 38677-1848, USA. ' Department of Chemical Engineering, University of Mississippi, MS 38677-1848, USA
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.
Keywords: gene expression; hair-cycle; hair growth; anagen; catagen; fractal analysis; bioinformatics.
International Journal of Bioinformatics Research and Applications, 2006 Vol.2 No.3, pp.249 - 258
Published online: 07 Aug 2006 *Full-text access for editors Access for subscribers Purchase this article Comment on this article