Following on from the completion of the human genome in 2003, the emergence of a comprehensive Omics pipeline, comprising multiple orthogonal platforms encompassing genomics, proteomics, metabolomics, transcriptomics and interactomics, has brought with it exponentially increasing volumes of experimental data arising from the use of a number of high throughput data-intensive technologies (e.g. mass spectrometry, microarray, NextGen sequencing) that have recently been developed. Whilst these data hold the key to an improved understanding of human health and disease, and should support the emerging field of personalized medicine, effective and efficient mining of this data is not without its trials and tribulations, including how to handle the complex information involved, how to integrate the data from a significant number of very heterogeneous platforms, what principles and standards must be adopted to ensure the veracity of the findings as well as potential ethical and funding issues.
In this presentation I will overview the Omics pipeline, present the concept of personalized medicine, discuss some of the problems that could arise in the handling of the “Big Data” generated in the road ahead and the role the human proteome organization (HUPO) has in addressing some of these problems.