Title :
Periodicity Detection in Small-Sample Gene-Expression Data
Author :
Mahata, Kaushik ; Mahata, Pritha
Author_Institution :
Univ. of Newcastle, Callaghan
Abstract :
Analysis of cell-cycle regulation, circadian rhythms, ovarian cycle, etc, demands finding periodicity in the biological data. In this work, we will consider gene expression data, which is usually quite noisy and comprise of small number of samples from very few periods (2 - 3). We propose a n on-parametric method for detecting the period and shape of the periodic signals (e.g., gene expressions for cell-cycles). We use a quadratic-optimization problem formulation in order to find the shape of the signal and the properties of periodicity to find the exact period. Finally, we show the results of applying this method on the gene expression data for human fibroblast cell cycles.
Keywords :
cellular biophysics; genetic algorithms; genetics; medical signal detection; cell-cycle regulation; circadian rhythms; human fibroblast cell cycles; on-parametric method; ovarian cycle; periodic signals; periodicity detection; quadratic-optimization problem formulation; small-sample gene-expression data; Australia; Cancer; Circadian rhythm; Computer science; Fast Fourier transforms; Fibroblasts; Gene expression; Humans; Organisms; Shape; Time-series microarray data; convex optimization; periodicity;
Conference_Titel :
Digital Signal Processing, 2007 15th International Conference on
Conference_Location :
Cardiff
Print_ISBN :
1-4244-0882-2
Electronic_ISBN :
1-4244-0882-2
DOI :
10.1109/ICDSP.2007.4288531