CAREER: Computational Tools for Fundamental Characterization and Inference of Genetic Interaction Networks

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The University of Minnesota-Twin Cities is awarded a grant by the NSF Faculty Early Career Development (CAREER) Program to support the development of computational approaches for understanding large-scale genetic interaction networks. Understanding the organization of biological systems and how it relates to function is one of the fundamental questions of modern molecular biology. A classical approach to characterizing cellular organization is to probe a cell with combinations of genetic perturbations and observe the resulting phenotype. This approach has recently been applied on a genome-wide scale in model organisms like yeast, where experimental technologies have enabled the construction of millions of combinatorial mutants. Preliminary studies hint that these data may provide an unprecedented view of cellular organization, but our ability to generate mutants and measure quantitative phenotypes has quickly surpassed our capacity for systematic interpretation of them. This project will support the development of computational infrastructure for addressing this need, including three specific objectives: (1) novel algorithms for comprehensive mining of genetic interaction network structure, (2) predictive models of genetic interactions from diverse genomic data within and across species, and (3) software tools for integrative analysis and visualization of genetic interaction networks to facilitate discovery.The research goals of the project are integrated with an educational component, which will address a critical need in interdisciplinary science: the issue of identifying talented students early enough such that they are able to establish a broad, but solid, foundation for interdisciplinary research. The PI will start a bioinformatics outreach program in which area high-school science and math teachers, particularly those from rural communities, are invited to participate in and develop their own educational programs highlighting recent successes and future directions in genomics and bioinformatics. The PI is also developing new computational biology courses at both the undergraduate and graduate level and involving undergraduate and graduate students in highly collaborative, interdisciplinary projects. More about the project can be found at http://www.cs.umn.edu/~cmyers.