Information integration approaches to network modeling – John Quackenbush


Two trends are driving innovation and discovery in biological sciences: technologies that allow holistic surveys of genes, proteins, and metabolites and the growing realisation that analysis and interpretation of the resulting requires an understanding of the complex phenotypic and environmental data regarding the samples from which they were derived. Further, the growing body of biological and biomedical information in the public domain provides outstanding opportunities 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 cancers and to explore how we can use biological data to begin to uncover the cellular networks and pathways that underlie human disease, building predictive models of those networks that may help to direct therapies.

Two trends are driving innovation and discovery in biological sciences: technologies that allow holistic surveys of genes, proteins, and metabolites and the growing realisation that analysis and interpretation of the resulting requires an understanding of the complex phenotypic and environmental data regarding the samples from which they were derived. Further, the growing body of biological and biomedical information in the public domain provides outstanding opportunities 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 cancers and to explore how we can use biological data to begin to uncover the cellular networks and pathways that underlie human disease, building predictive models of those networks that may help to direct therapies.”

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