Systematic analyses of interactome networks
By: by Qianru Li
Published: 2008
Language: eng
Number of pages: 227
Description: A prerequisite to understand global properties of cellular systems is to map as completely and accurately as possible the network of all physical interactions that occur in a physiologically relevant dynamic range between all macromolecules in an organism, i.e ., the "interactome". Knowing when, where and for what purpose protein-protein interactions occur in vivo is one of the ultimate goals of mapping interactomes. Despite the current intensive analyses and wide applications of several interactome maps available for different organisms, many questions remain unanswered, such as the quality and coverage of these maps, the dynamic aspects of the molecular interactions and the relationship between network models and human disease. My dissertation study focuses on three important issues with regard to the generation and analyses of comprehensive interactome networks. First, using Saccharomyces cerevisiae as a model organism, I developed a novel framework combining both experimental and computational approaches to improve the yeast genome annotation. An accurate definition of the complete set of protein-encoding open reading frames is crucial to completing the scaffold of any interactome networks. Second, I contributed significantly towards cloning the first version of Caenorhabditis elegans promoterome, which will greatly facilitate examining the spatial and temporal aspects of the Caenorhabditis elegans interactome network. Third, I contributed in a team effort to develop a new technology platform to systematically study the effects of disease-associated mutations on the physical and functional interactions mediated by human disease-associated gene products.

This platform allows high-throughput experimental exploration of local perturbations on the interactome. Bridging the functional consequences of disease-associated mutations with complex interactome network models should eventually lead to better understanding of human disease.
Notes: "July 2008."

Thesis (Ph.D., Division of Medical Sciences (Genetics))--Harvard University, 2008.

Includes bibliographical references.