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As omics science moves forward, identifying methodologies and applications based on specific types of omic data, as well as their integration, becomes increasingly important as it provides new insights to be rapidly tested in basic or applied research.  The Omics Integration in Biology and Medicine Workshop, held June 19-20, addressed many of the challenges and potential benefits from integrative data analysis and how to overcome current barriers. Sponsored by the National Heart, Lung and Blood Institute’s Proteomics Centers Program and also the National Cancer Institute’s Office of Cancer Clinical Proteomics; the workshop focused on the emerging field of integrating disparate omic data from genomics, proteomics, glycomics, etc. in order to better understand key biological processes and also improve clinical practice. Discussants identified technical and biological barriers in omic integration, with solutions to build a consensus towards data integration in bioscience and to better define phenotypes.

The workshop was framed by two research findings/approaches: Framingham study and the recently published study from the research group of Dr. Mike Snyder from Stanford University.  In the Snyder study in depth proteomic, genomic, metabolomics analysis was performed to measure the variation in health of one individual, Mike Snyder, over the course of more than one year. While in the Framingham Study (http://www.framinghamheartstudy.org/) study three cohorts of populations have been followed to understand the role of cardiovascular disease.  Framed by these studies the participants discussed what are seen as the major challenges facing integrative analysis and advances being made in both research and the clinic through a series of case-studies focusing on protein misfolding; cancer, and the role of informatics in integration. 

To find out more about what the discussants viewed as the most pressing challenges, you can view the full coverage of the event on NIH Videocast: Day 1 and Day 2.