Analysis of Time-Series Gene Expression Data: Methods, Challenges, and Opportunities

• DOI: 10.1146/annurev.bioeng.9.060906.151904
• Publication Date: 2007-06-25T17:16:31Z
• Authors: I.P. Androulakis; E. Yang; R.R. Almon
• Keywords: Scope (computer science); Expression (computer science)

Monitoring the change in expression patterns over time provides distinct possibility of unraveling mechanistic drivers characterizing cellular responses. Gene arrays measuring level mRNA thousands genes simultaneously provide a method high-throughput data collection necessary for obtaining scope required understanding complexities living organisms. Unraveling coherent complex structures transcriptional dynamics is goal large family computational methods aiming at upgrading information content time-course gene data. In this review, we summarize qualitative characteristics these approaches, discuss main challenges that type present, and, finally, explore opportunities context developing models response.