Review

Integrating post-genomic approaches as a strategy to advance our understanding of health and disease

Jing Tang¹, Chong Y Tan², Matej Oresic^1* and Antonio Vidal-Puig^2*

• * Corresponding authors: Matej Oresic matej.oresic@vtt.fi - Antonio Vidal-Puig ajv22@cam.ac.uk

Author Affiliations

¹ VTT Technical Research Centre of Finland, Tietotie 2, PO Box 1000, FIN-02044, Espoo, Finland

² Metabolic Research Laboratories, Level 4, Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK

For all author emails, please log on.

Genome Medicine 2009, 1:35 doi:10.1186/gm35

Published: 30 March 2009

Abstract

Following the publication of the complete human genomic sequence, the post-genomic era is driven by the need to extract useful information from genomic data. Genomics, transcriptomics, proteomics, metabolomics, epidemiological data and microbial data provide different angles to our understanding of gene-environment interactions and the determinants of disease and health. Our goal and our challenge are to integrate these very different types of data and perspectives of disease into a global model suitable for dissecting the mechanisms of disease and for predicting novel therapeutic strategies. This review aims to highlight the need for and problems with complex data integration, and proposes a framework for data integration. While there are many obstacles to overcome, biological models based upon multiple datasets will probably become the basis that drives future biomedical research.