Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/114850
Title: DATA-DRIVEN BAYESIAN APPROACH TO THE ANALYSIS OF CELL SIGNALLING NETWORKS IN SYNERGISTIC LIGAND-INDUCED NEURITE OUTGROWTH IN PC12 CELLS
Authors: SEOW KOK HUEI
Keywords: Systems Biology, Bayesian Networks, Synergism, Cell Signalling, Neurite, PC12 Cells
Issue Date: 23-Jan-2014
Source: SEOW KOK HUEI (2014-01-23). DATA-DRIVEN BAYESIAN APPROACH TO THE ANALYSIS OF CELL SIGNALLING NETWORKS IN SYNERGISTIC LIGAND-INDUCED NEURITE OUTGROWTH IN PC12 CELLS. ScholarBank@NUS Repository.
Abstract: The concept of synergism, where the combinatorial effects of the components are greater than the sum of the constituent parts, is of high importance in both drug therapeutics and the regulation of cellular behaviours. However, mathematical modeling approaches that can analyze such multi-variant synergistic systems are lacking. In this thesis, the mechanism underlying synergistic neurite outgrowth, an important process in both neuronal development and treatment of neurodegenerative diseases, is investigated at a systems-level. The differential involvement of various signalling pathways in regulating neurite outgrowth was first investigated in three systems, EGF-PACAP, FGFb-PACAP, and NGF-PACAP. A modified Bayesian modeling approach was then used to gain insights into the cross-talks between signalling pathways that contributed to such synergistic behaviour in the NGF-PACAP system. This proof-of-concept study demonstrated the practicality of the proposed modeling approach and can essentially be applied to the analysis of other multi-ligand systems beyond the scope of this thesis.
URI: http://scholarbank.nus.edu.sg/handle/10635/114850
Appears in Collections:Ph.D Theses (Open)

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