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Bonnie Berger. Dong, Yu-An, 1974- Massachusetts Institute of Technology. Dept. of Mathematics. Massachusetts Institute of Technology. Department of Mathematics 2005-09-27T19:05:50Z 2005-09-27T19:05:50Z 2004 2005 http://hdl.handle.net/1721.1/28925 60503962 Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, February 2005. Includes bibliographical references (leaves 116-117). Complex networks arise in diverse areas of natural and social sciences and network topology is a key determinant of such systems. In this work we investigate the protein-protein interaction network of the KSHV herpesvirus, which is the first viral system available, and compare it to a prototypical cellular system. On the local level, we investigated the relationship between interaction and sequence evolution, functional class, phylogenetic class, and expression profiles. On the global level, we focused on large-scale properties like small-world, scale-free, and attack tolerance. Major differences were discovered between viral and cellular systems, and we were able to pinpoint directions for further investigation, both theoretically and experimentally. New approaches to discover functional associations through interaction patterns were also presented and validated. To put the KSHV network in the context of host interactions, we were able to predict interactions between KSHV and human proteins and use them to connect the KSHV and human PPI networks. Though simulations, we show that the combined viral-host network is distinct from and superior to equivalent randomly combined networks. Our combined network provides the first-draft of a viral-host system, which is crucial to understanding viral pathogenicity. In a separate chapter, the results of a project combining experiments and bioinformatics are also presented. We were able to report [approximately]30 new yeast protein-protein interactions and pinpoint the biological significance of some of those interactions. The methodology of yeast two-hybrid itself is also tested and assessed. by Yu-An Dong. Ph.D. 117 leaves 6424527 bytes 6438756 bytes application/pdf application/pdf en_US Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Mathematics. Statistical analysis of protein interaction network topology Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="fc73df55-44bb-4fb0-8155-80d63f5179bb"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>en_US</Language> <Title>Statistical analysis of protein interaction network topology</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2005</PublicationDate> <Authors> <Author> <DisplayName>Dong, Yu-An, 1974-</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Mathematics.</Keyword> <Abstract>Complex networks arise in diverse areas of natural and social sciences and network topology is a key determinant of such systems. In this work we investigate the protein-protein interaction network of the KSHV herpesvirus, which is the first viral system available, and compare it to a prototypical cellular system. On the local level, we investigated the relationship between interaction and sequence evolution, functional class, phylogenetic class, and expression profiles. On the global level, we focused on large-scale properties like small-world, scale-free, and attack tolerance. Major differences were discovered between viral and cellular systems, and we were able to pinpoint directions for further investigation, both theoretically and experimentally. New approaches to discover functional associations through interaction patterns were also presented and validated. To put the KSHV network in the context of host interactions, we were able to predict interactions between KSHV and human proteins and use them to connect the KSHV and human PPI networks. Though simulations, we show that the combined viral-host network is distinct from and superior to equivalent randomly combined networks. Our combined network provides the first-draft of a viral-host system, which is crucial to understanding viral pathogenicity. In a separate chapter, the results of a project combining experiments and bioinformatics are also presented. We were able to report [approximately]30 new yeast protein-protein interactions and pinpoint the biological significance of some of those interactions. The methodology of yeast two-hybrid itself is also tested and assessed.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>