Location: Maxwell-Dworkin G125, 33 Oxford Street, Cambridge, MA 02138

Time: Informal lunch with speaker, 12:30pm. Talk, 1:00pm.

Title: The Network Effect: Integrative Systems Approaches to Modeling Biological Processes

Abstract:

Two trends are driving innovation and discovery in biological sciences: technologies that allow holistic surveys of genes, proteins, and metabolites, and the growing realization that analysis and interpretation of the results requires an understanding of the complex factors that mediate the link between genotype and phenotype. The growing body of biological and biomedical information, driven by an exponential drop in the cost of generating genomic data, provides an outstanding opportunity for leveraging what we already “know” in a systematic way to understand the problems we are studying. Here, I will provide an overview of some of the methods we are using to investigate the complexities of human phenotypes and to explore how we can use biological data to uncover the cellular networks and pathways that underlie human disease, building predictive models of those networks that may help to direct therapies.

Speaker bio:

John Quackenbush received his PhD in 1990 in theoretical physics from UCLA, working on string theory models. Following two years as a postdoctoral fellow in physics, he received a Special Emphasis Research Career Award from the National Center for Human Genome Research to work on the Human Genome Project. He spent two years at the Salk Institute working on developing physical maps of human chromosome 11 and two years at Stanford University working on new laboratory and computational strategies for sequencing the human genome. In 1997 he joined the faculty of The Institute for Genomic Research (TIGR), where his focus began to shift to post-genomic applications with an emphasis on microarray analysis. Using a combination of laboratory and computational approaches, Quackenbush and his group developed analytical methods based on integration of data across domains to derive biological meaning from high-dimensional data. In 2005, he was appointed Professor of Biostatistics and Computational Biology and Professor of Cancer Biology at the Dana-Farber Cancer Institute (DFCI) and Professor of Computational Biology and Bioinformatics at the Harvard School of Public Health. Since that time, his work has increasingly focused on the analysis of human cancer using systems-based approaches to understanding and modeling biological problems. In 2009 he launched the Center for Cancer Computational Biology (CCCB) at the DFCI, which provides broad-based bioinformatics support to the local research community using a collaborative consulting model.

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