Descrição Booleana para eventos celulares: construção de redes, topologia e análise dinâmica

Detalhes bibliográficos
Ano de defesa: 2012
Autor(a) principal: Bugs, Cristhian Augusto
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Tese
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Santa Maria
BR
Física
UFSM
Programa de Pós-Graduação em Física
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
ABA
Link de acesso: http://repositorio.ufsm.br/handle/1/3907
Resumo: This work presents a methodology to describe the dynamics and topology of biological regulatory networks through the application of graph theory. We model these networks using Boolean rules and simulations performed with algorithms implemented in MATHEMATICA 7.0. Through this methodology, we characterize the regulatory network of opening and closing of the stomata of a plant by abscisic acid (ABA), including the relationships between the network s elements during the dynamics and the description of the state-space by comparing each one of its elements. For the state of cellular replicative senescence in humans, the goal is to describe a regulatory network of proteins involving the mechanisms of Shelterin complex, DNA double-strand break signaling, and the cell cycle arrest in G1 phase. The network topology must involve a combination of pathways and modules to ensure the stability of the signal and the permanent cell-cycle arrest. The state senescent is also characterized by establishing a secretory phenotype (SASP) with both beneficial and harmful effects for the organism. Different pathways are identified along with the activation of NF-kB in the regulation of these phenotypes and in this sense, a regulatory network to regulate the SASP in replicative senescence is proposed and the main consequences of the SASP for human colon are identified via analysis of microarray data related to normal colon, inflamed colon, colonic adenoma and carcinoma of the colon.