Keystone Symposia

This meeting took place in 2012

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Complex Traits: Genomics and Computational Approaches (B5)

Organizer(s) Eric Schadt, Stephen H. Friend and Iya G. Khalil
February 20—25, 2012
Beaver Run Resort • Breckenridge, CO USA
Abstract Deadline: Oct 20, 2011
Late Abstract Deadline: Dec 1, 2011
Scholarship Deadline: Oct 20, 2011
Early Registration Deadline: Jan 4, 2012

Supported by the Directors' Fund

Summary of Meeting:
Complex traits are driven by constellations of genetic and environmental factors interacting in complex ways. Genetic and environmental perturbations do not directly lead to disease but, rather, impact molecular processes that underlie physiological states associated with disease. Therefore, in order to develop a complete understanding of complex traits like disease, biological systems must be queried in a comprehensive fashion in multiple dimensions. Different data dimensions like genotype, gene expression, proteomic and metabolomic offer complementary views that are useful individually and exceptionally valuable collectively. Without mastering the large-scale molecular data that underlies pathophysiological states, without sophisticated mathematical algorithms capable of data integration, and without an appropriate informatics infrastructure to apply these algorithms and translate the results into manageable bites of information that can be consumed by physicians and patients, efforts to realize the dream of personalized medicine will be difficult to achieve. Towards this end of realizing the promise of personalized medicine, the Keystone Symposia meeting on Complex Traits: Genomics and Computational Approaches will focus on three different areas: 1) methods for integrating diverse, large-scale, high-dimensional data with clinical phenotypes to construct predictive models (e.g., networks) of disease; 2) application of integrative biology approaches that combine large-scale molecular and clinical phenotype information to elucidate the underlying causes of disease and to prioritize drug targets and biomarkers; and 3) technological advances that will drive a dramatic explosion in data that will enable better models of disease and solutions to address the problem of how to enable others to share big data, interact with complex models and refine those models to improve our understanding of disease and associated biological processes.

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Early Career Investigator Travel Award Recipients

Tesfaye B. Mersha
University of Cincinnati, USA

Keystone Symposia Future of Science Fund Scholarship Recipients

Jonathan R. Karr
Icahn School of Medicine at Mount Sinai, USA