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A Gene-Complete Computational Model of Yeast

$800,000DP1FY2010ODNIH

Stanford University, Stanford CA

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Abstract

DESCRIPTION Abstract The target of this proposal is to build a computational model that can simulate a complete life cycle of a single yeast cell, taking into account all of the annotated genes. This has been called "the ultimate test of understanding a simple cell" and will revolutionize how we view biology, by allowing us to examine interactions between major cellular processes which have never been studied before. We will demonstrate this point, integrating computational modeling and experimental biology, in a detailed study of aging and lifespan control. Several intellectual challenges will have to be addressed to complete the proposed work successfully. For example, a major component of our effort to build a whole-cell model will depend on the development of new modeling approaches, applicable at a large scale. Additionally, methods for the integration of models for different types of biological processes, each of which may be best described using different representation, will be critical. Fortunately, the particular expertise of the P.I. is in modeling a variety of cellular processes, and in particular integrating different network models at the large scale. Our proposed work aims not only to pass the "ultimate test" of building a whole-cell computer model, but to make it accessible to the scientific community and the general public through a user-friendly web interface. One deliverable of the project will be a web-based platform which will allow the user to track and perturb biological processes such as DNA replication, RNA transcription and regulation, protein synthesis, metabolism and cell division. For scientists, the platform will have advanced user options, so that other researchers can adapt our methods to whichever cell type(s) they prefer. We anticipate that this could lead to a broad implementation of research which uses computational modeling and simulation to guide experimental programs and biological discovery. Public Health Relevance The broad goal of this res

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