|Support type:||Scholarships in Brazil - Doctorate|
|Effective date (Start):||December 01, 2009|
|Effective date (End):||February 28, 2013|
|Field of knowledge:||Biological Sciences - Genetics - Animal Genetics|
|Principal Investigator:||César Martins|
|Grantee:||Guilherme Targino Valente|
|Home Institution:||Instituto de Biociências (IBB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil|
Nowadays the biological systems have been analyzed under several research foci, including the system biology. This area focus to describe and understand the relationship between biotic and abiotic factors using the graph theory. The protein interactions are target interactions to the system biology because they are the most abundant biomolecular interactions within a cell. Thus, this thesis reported the development of a computational algorithm to predict protein-protein interactions for all species or protein sets. The machine learning technique (sub-area of artificial intelligence) were used to develop and apply this method, giving effective results to predict protein-protein interaction for more than 80 different species, including parasite-host associations. This new predictor was applied to the proteome set of zebrafish (Danio rerio) and humans (Homo sapiens), generating the protein-protein interactions for both species. Evolutionary aspects of the protein interactions were studied in a broad context and the focus was directed to the sub-network involved in the vertebrate sex determination and differentiation. The results reported a low conservation of those graphs across the evolution in a general view or for the sub-network related to the vertebrate sex determination and differentiation. Moreover, it was reported at least one conserved hub between both sub-networks, to be further evaluated by experimental procedures. Anyway, the data showed that the predictor here reported may be very useful for several research areas and it is desirable for large-scale prediction procedures. Furthermore, the evolutionary aspects discussed in this thesis open new perspectives concerning system biology and evolutionary pathways of vertebrate sex determination and differentiation.