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• W2534446951 endingPage "e2542" @default.
• W2534446951 startingPage "e2542" @default.
• W2534446951 abstract "Breast cancer (BC) is one of the leading cause of death among females worldwide. The increasing incidence of BC is due to various genetic and environmental changes which lead to the disruption of cellular signaling network(s). It is a complex disease in which several interlinking signaling cascades play a crucial role in establishing a complex regulatory network. The logical modeling approach of René Thomas has been applied to analyze the behavior of estrogen receptor-alpha (ER-α) associated Biological Regulatory Network (BRN) for a small part of complex events that leads to BC metastasis.A discrete model was constructed using the kinetic logic formalism and its set of logical parameters were obtained using the model checking technique implemented in the SMBioNet software which is consistent with biological observations. The discrete model was further enriched with continuous dynamics by converting it into an equivalent Petri Net (PN) to analyze the logical parameters of the involved entities.In-silico based discrete and continuous modeling of ER-α associated signaling network involved in BC provides information about behaviors and gene-gene interaction in detail. The dynamics of discrete model revealed, imperative behaviors represented as cyclic paths and trajectories leading to pathogenic states such as metastasis. Results suggest that the increased expressions of receptors ER-α, IGF-1R and EGFR slow down the activity of tumor suppressor genes (TSGs) such as BRCA1, p53 and Mdm2 which can lead to metastasis. Therefore, IGF-1R and EGFR are considered as important inhibitory targets to control the metastasis in BC.The in-silico approaches allow us to increase our understanding of the functional properties of living organisms. It opens new avenues of investigations of multiple inhibitory targets (ER-α, IGF-1R and EGFR) for wet lab experiments as well as provided valuable insights in the treatment of cancers such as BC." @default.
• W2534446951 created "2016-10-28" @default.
• W2534446951 creator A5012043305 @default.
• W2534446951 creator A5012918179 @default.
• W2534446951 creator A5053624272 @default.
• W2534446951 creator A5057781258 @default.
• W2534446951 creator A5060980511 @default.
• W2534446951 creator A5091246206 @default.
• W2534446951 date "2016-10-20" @default.
• W2534446951 modified "2023-10-16" @default.
• W2534446951 title "Formal modeling and analysis of ER-αassociated Biological Regulatory Network in breast cancer" @default.
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