Analysis of temporal gene expression profiles using time-dependent music algorithm

Nidhal Bouaynaya, Dan Schonfeld, Radhakrishnan Nagarajan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Identifying periodically expressed genes and their subsequent transcriptional circuitry can shed new lights in studying the molecular basis of many diseases including cancer; and subsequently provide potential drug targets to treat them. Classical approaches for detecting periodically expressed transcripts in paradigms such as cell-cycle implicitly assume the given data to be stationary. However, it has been experimentally shown that modulation in the magnitude of gene expression is ubiquitous and defy stationary assumptions. In this paper, we formulate the problem of estimating the frequencies of multicomponent amplitude modulated (AM) signals as a hypothesis testing problem based on a time-dependent extension of the MUSIC algorithm. We subsequently propose a test statistic to detect periodic components in AM time-series. The power of the proposed algorithm is assessed in synthetic test signals and in real cell-cycle gene profiles extracted from microarray data.

Original languageEnglish (US)
Title of host publication2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009 - Minneapolis, MN, United States
Duration: May 17 2009May 21 2009

Publication series

Name2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009

Other

Other2009 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2009
Country/TerritoryUnited States
CityMinneapolis, MN
Period5/17/095/21/09

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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