Why Networks Matter: Embracing Biological Complexity
Hear Harvard University's Dr. John Quackenbush share multiple examples illustrating the importance of network models. He draws on his work in cancer, chronic obstructive pulmonary disease, and the analysis of data from 38 tissues provided by the Genotype-Tissue Expression project. Learn how researchers can use these models to explore the development and progression of the disease and new ways to identify therapeutics.
One of the central tenets of biology is that our genetics (our genotype) influence the physical characteristics we manifest (our phenotype). With more than 25,000 human genes and more than 6,000,000 common genetic variants mapped in our genome, finding associations between our genotype and phenotype is an ongoing challenge.
Genome-wide association studies have found thousands of small effect-size genetic variants associated with phenotypic traits and disease. Genes and genetic variants work together in complex regulatory networks that help define phenotypes and mediate phenotypic transitions. Dr. Quackenbush’s team has found that these networks and their structures provide unique insight into how genetic elements interact with each other. Their designs have predictive power for identifying critical processes in health and disease and for identifying potential therapeutic targets.
To view upcoming speakers or recordings of past presentations, visit the CBIIT Data Science Seminar Series webpage.
The Data Science Seminar Series presents talks from innovators in the cancer research and informatics communities both within and outside of NCI.
Dr. Quackenbush is a computational biology and bioinformatics professor and Chair of the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. He is also a professor at the Dana-Farber Cancer Institute. Among his honors are being recognized as the White House Open Science Champion of Change (2013) and elected to the National Academy of Medicine (2022).
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