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Modern research requires collaboration among geographically distributed scientists. This collaborative model is transforming scientific discovery by enabling sharing and validation of data across institutions. Informatics infrastructures are being developed to support cancer research, endowing scientists with the ability to capture and share data with remote collegues. A critical challenge presented by such infrastructures is the development of a curation model for the science data. While considerable emphasis has been placed on developing grid infrastructures, few are addressing the curation aspects crucial to creating a useful scientific knowledgebase. The United States National Cancer Institute’s (NCI) Early Detection Research Network (EDRN) is a distributed network of research institutions focused on the discovery of cancer biomarkers. In this paper, we describe our work building a data collection and curation infrastructure on top of the existing EDRN bioinformatics data grid. The approach involves normalizing curated data through the use of a common information model for cancer biomarker research. We argue that such a model is critical to ensuring that data can be combined into an integrated knowledge system. Furthermore, we argue that human curators with backgrounds in both informatics and science play a critical role in the overall value of the EDRN knowledge-base.

AN EXTENSIBLE BIOMARKER CURATION APPROACH AND SOFTWARE INFRASTRUCTURE FOR THE EARLY DETECTION OF CANCER