Within the field of genetic medicine, biology has evolved from an observational science to one capable of testing hypotheses, and now to a science that makes copious use of mathematical modeling and analysis to understand complex, systematic interactions. Computational biology is a marriage of biology, mathematics and computer science that provides valuable insights in the form of:
- predictive models of complex biological systems
- statistical analyses and pattern recognition in large data sets
- analysis of risk factors in clinical and genetic sciences
In the Weill Cornell Department of Genetic Medicine, large datasets produced from cutting-edge genomic and transcriptomic studies provide the basis for the development of our computational biology tools. These resources facilitate the implementation of our genome-wide association studies and transcriptional signatures, which define the biological response to environmental stressors and pathophysiological conditions (such as cigarette smoking and chronic obstructive pulmonary disease [COPD]). Our computational biologists play a crucial role performing this essential translational research in the Department of Genetic Medicine.