Genomic Signal Processing: The Salient Issues

Abstract

This paper considers key issues in the emerging field of genomic signal processing and its relationship to functional genomics. It focuses on some of the biological mechanisms driving the development of genomic signal processing, in addition to their manifestation in gene-expression-based classification and genetic network modeling. Certain problems are inherent. For instance, small-sample error estimation, variable selection, and model complexity are important issues for both phenotype classification and expression prediction used in network inference. A long-term goal is to develop intervention strategies to drive network behavior, which is briefly discussed. It is hoped that this nontechnical paper demonstrates that the field of signal processing has the potential to impact and help drive genomics research.