Innovative computational methods for transcriptomic data analysis

Abstract

The tools of molecular biology and the evolving tools of genomics can now be exploited to study the genetic regulatory mechanisms that control cellular responses to a wide variety of stimuli. These responses are highly complex, and involve many genes and gene products. The main objectives of this paper are to describe a novel research program centered on understanding these responses by developing powerful graph algorithms that generate distilled gene sets, producing high performance implementations utilizing cutting-edge platforms, employing these implementations to identify gene sets suggestive of coregulation, and performing sequence analysis and genomic data mining to examine, winnow and highlight the most promising gene sets for more detailed investigation. As a case study, we describe our work aimed at elucidating genetic regulatory mechanisms that control cellular responses to low dose ionizing radiation (IR). We use genome-scale gene expression data after IR exposure in vivo to identify the pathways that are activated or repressed as a tissue responds to the radiation insult. Knowledge of these pathways should help clarify and interpret physiological responses to IR, which will advance our understanding of how IR exposures pose an increased risk to human health. Copyright 2006 ACM.