Computational Genomic Epidemiology of Cancer (CoGEC) Training Program

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PROJECT SUMMARY/ABSTRACT Undertaking innovative cancer research requires input from teams of scientists with a mixture of backgrounds, including molecular biology, oncology, medicine, epidemiology, biostatistics, genomics/genetics, bioinformatics, computer science and artificial intelligence. Researchers with interdisciplinary training across these fields are extremely valuable to such teams, as they can act as conduits for the integrated work necessary to accomplish some of the most promising and forward-looking cancer research. Due to the exclusive nature of training within these fields, however, there are limited opportunities for investigators to obtain the knowledge that bridges these disciplines. To help remedy this problem, we propose here the continuation of this T32 program to provide postdoctoral training in the Computational Genomic Epidemiology of Cancer (CoGEC) at the Case Comprehensive Cancer Center. The CoGEC training program defines a novel, transdisciplinary area of training at the intersection of cancer research, epidemiology, biostatistics, genetics, and computer science. The program’s structure is defined by three key requirements. First, all trainees will have the opportunity to take a specialized core curriculum of five courses to fill in the gaps of their previous training if necessary. Second, the trainees will undertake additional didactic experiences selected to complement their educational and research background. Third, all trainees will obtain research experience by collaborating with multiple mentors on high-level computational genomic epidemiology of cancer projects. As an extension of this research experience, each trainee will be required to write and defend an NIH grant proposal. Cancer researchers obtaining training in this program will have the skills vital to deciphering the complex pathways comprising genetic and environmental risk factors for disease. In doing so, their knowledge and findings will be translated into improved cancer understanding, prevention and treatment.