Computational and bioinformatic analysis of complex biochemical pathways

Abstract

Computational and bioinformatic methodologies for the representation, analysis and simulation of complex biochemical pathways, i.e., metabolic and signal transduction pathways, have been established for system-level understanding of biological systems. In Chapter 2, the integrated environment is developed for managing information on the metabolic reaction network and for quantitatively analyzing metabolic fluxes; this renders it possible to implement quantitative in silico simulations of metabolic pathways for understanding the metabolic status and for devising the metabolic engineering strategies. In Chapter 3, a rigorous method is established for systematically identifying biochemical reactions, or metabolic pathways. It is based on the mathematically exact, graph-theoretic method for the identification, i.e., determination, of the mechanisms of complex chemical reactions. It has been amply demonstrated that the method is applicable to biochemical reactions and is capable of characterizing the underlying network structure and function of the reaction system defined. In Chapter 4, the unified approach is proposed for synergistically, or complementarily, identifying multiple flux distributions in metabolic flux analysis and multiple metabolic pathways in structural pathway analysis. The results from applying the proposed approach to the E. coli model demonstrate its profound efficiency and efficacy. These results also reveal the surprising adaptability and robustness of the intricate cellular network as a key to cell survival against environmental or genetic change. In Chapter 5, the conceptual framework is presented for both qualitatively and quantitatively understanding the cell signaling behavior by resorting to Petri nets. The mechanisms and dynamics of the network have been investigated by applying the method based on the resultant framework to the signal transduction system induced by IL-1, TNF-α, and EGF. The results provide a proof of the principle for ...