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Abstract
Abstract Despite considerable progress in prevention and treatment, cancer remains the second leading cause of death in the United States. Cancer researchers around the world are generating massive amounts of clinical and genetic data, although due to its volume, complexity and lack of centralization, much is left unanalyzed. Big Data backed by powerful analytics holds the key to gain important insights from such high volume, variety and velocity data enabling a new understanding of cancer from molecular biology through clinical management. It provides opportunities to ask complex questions and identify novel knowledge from existing data including the study of genetics of an individual's cancer cells, on her response to treatment and sensitivity to side effects. In this session, we will understand the recent developments in Big Data Analytics platforms and how this transformative technology can be harnessed to leverage multidimensional data for developing new preventive measures, diagnostic tools and interventions in cancer research. We will also review success stories from early adopters of Big Data in cancer and highlight the challenges and opportunities for future research and development. Learning objectives: By the end of this session, the participants should be able to: 1.) Understand the fundamental concepts and principles of Big Data technology 2.) Identify community-based open-source Big Data informatics resources and tools 3.) Recognize the importance of Big Data in cancer prevention research Citation Format: Jyotishman Pathak. The era of big data informatics for clinical and translational research in cancer prevention. [abstract]. In: Proceedings of the Twelfth Annual AACR International Conference on Frontiers in Cancer Prevention Research; 2013 Oct 27-30; National Harbor, MD. Philadelphia (PA): AACR; Can Prev Res 2013;6(11 Suppl): Abstract nr ED03-02.
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