Identification of hair cycle-associated genes from time-course gene expression profile using fractal analysis

Sunil K. Mathur, Atul M. Doke, Ajit Sadana

Research output: Contribution to journalArticle

4 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)249-258
Number of pages10
JournalInternational Journal of Bioinformatics Research and Applications
Volume2
Issue number3
DOIs
StatePublished - 2006

Keywords

  • Anagen
  • Catagen
  • Gene expression
  • Hair-cycle

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Clinical Biochemistry
  • Health Information Management

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