A kernel-based integration of genome-wide data for clinical decision support.

ABSTRACT:

Background

Although microarray technology allows the investigation of the transcriptomic make-up of a tumor in one experiment, the transcriptome does not completely reflect the underlying biology due to alternative splicing, post-translational modifications, as well as the influence of pathological conditions (for example, cancer) on transcription and translation. This increases the importance of fusing more than one source of genome-wide data, such as the genome, transcriptome, proteome, and epigenome. The current increase in the amount of available omics data emphasizes the need for a methodological integration framework.

Methods

We propose a kernel-based approach for clinical decision support in which many genome-wide data sources are combined. Integration occurs within t

SUBMITTER: Daemen A 

PROVIDER: S-EPMC2684660 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature