2017 Graybill Conference on Statistical Genomics and Genetics

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This award supports participation in the 2017 Graybill Conference on Statistical Genomics and Genetics, held June 5-7, 2017 on the campus of Colorado State University, Fort Collins, Colorado. The conference is co-sponsored by the American Statistical Association Section on Statistics in Genomics and Genetics. The program consists of invited talks, a contributed poster session, and a student poster competition. The goal of the conference is to provide an opportunity for quantitative scientists and practitioners in the biological sciences to generate and share ideas for new creative research in statistics and genomics or genetics; to exchange knowledge on frontier statistical methodologies for problems rising from genomics and genetics; to stimulate professional networking opportunities; and to provide young researchers with exposure for their work.The last decade has witnessed the rapid advancement of high-throughput technologies and the generation and storage of massive data sets. A huge number of new challenges in analyzing, modeling, and interpreting these massive data have arisen, forcing transformative change on research in biological and medical sciences in general, and genomics and genetics in particular. To meet those challenges and provide reliable approaches, statistical genomics and genetics have emerged from traditional statistics and have become indispensable tools for modern research in the biological and medical sciences, also paving the road to many important biological and medical discoveries in the last few years. On the other hand, novel problems arising in genomics and genetics have also motivated many new statistical concepts, models, and methodologies. Statistical genomics and genetics have been growing remarkably fast and apply to an increasing number of topics in both fields. They are now essential parts of modern biological and medical research and also generate important research topics within statistics. Exposure and understanding of the motivating problems, newly-developed models and methods, and working protocols are extremely useful for researchers in the quantitative sciences, including bioinformatics, computer science, and statistics. For more information, see the conference website at http://graybill.wolpe2.natsci.colostate.edu/