{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Evolution of Complexity in Gene Regulatory Networks During Host-Parasite Coevolution","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/77321"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"Robustness, defined as tolerance to perturbations such as mutations and environmental fluctuations, is pervasive in biological systems. However, robustness often coexists with its counterpart, evolvability - the ability of perturbations to generate new phenotypes. Previous models of gene regulatory network evolution have shown that robustness evolves under stabilizing selection, but in more realistic scenarios such as coevolution, it may be advantageous to evolve sensitivity, i.e. for some mutations to change the phenotype. Furthermore, it is unclear how robustness and evolvability will emerge in common coevolutionary scenarios. In this dissertation, we consider three different two-species models of coevolution involving one host and one parasite population. First, we developed a two-population (host, parasite) model to investigate how robustness and evolvability become distributed within a network under antagonistic coevolution. We found that sensitivity follows a pattern, similar to that of the game \u00e2\u20ac\u0153whack-a-mole\u00e2\u20ac , in which sensitive sites mutate, thus becoming insensitive, but new sensitive sites emerge to take their place. Second, we developed a host-virus interaction model focusing on host resistance and viral pathogenicity which depend on quite different evolutionary conditions. Viruses may evolve cell entry strategies that use small receptor binding regions, represented by low complexity binding in our model. Our modeling results suggest that if the virus adopts a strategy based on binding to low complexity sites on the host receptor, the host will select a defense strategy at the protein (receptor) level, rather than at the level of the regulatory network - a virus-host strategy that appears to have been selected most often in nature. Lastly, we developed a model of the host innate immunity evolution in the context of host-virus coevolution. After viruses enter host cells, they interfere with innate immune systems via protein-protein interactions such as molecular mimicry of various host proteins involved in the immunity. We found that depending on different viral mechanisms for pathogenicity, hosts evolved to optimize the use of 1) mutations at protein-protein interaction sites to avoid mimicry and 2) environmental robustness in the innate immune systems imposed by viral disruption of the immune systems."},{"label":"dcterms.available","value":"2017-09-20T16:52:30Z"},{"label":"dcterms.contributor","value":"Levy, Sasha"},{"label":"dcterms.creator","value":"Shin, Jeewoen"},{"label":"dcterms.dateAccepted","value":"2017-09-20T16:52:30Z"},{"label":"dcterms.dateSubmitted","value":"2017-09-20T16:52:30Z"},{"label":"dcterms.description","value":"Department of Applied Mathematics and Statistics"},{"label":"dcterms.extent","value":"132 pg."},{"label":"dcterms.format","value":"Application/PDF"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/77321"},{"label":"dcterms.issued","value":"2016-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2017-09-20T16:52:30Z (GMT). No. of bitstreams: 1\nShin_grad.sunysb_0771E_13073.pdf: 11430708 bytes, checksum: 3fcd2a3c6609cbf256cb2c8186a0330d (MD5)\n  Previous issue date:    1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"Evolution & development -- Applied mathematics"},{"label":"dcterms.title","value":"Evolution of Complexity in Gene Regulatory Networks During Host-Parasite Coevolution"},{"label":"dcterms.type","value":"Dissertation"},{"label":"dc.type","value":"Dissertation"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/11%2F77%2F97%2F117797715082361796463371413654059132202/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/11%2F77%2F97%2F117797715082361796463371413654059132202","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}