| Summary: | 碩士 === 國立交通大學 === 生醫工程研究所 === 106 === According to Darwinism, the adaptive mechanism will force species to do all the necessary needs to adapt better during the changing of environment. According to the genetic mechanism, a better genetic signature will survive and reproduce to the next generation. . In this thesis, we propose a computational simulator for the analysis of mutation and evolution regarding influenza A viruses (IAV). The objective of this simulator is two-fold: (a) a retrospective study of IAV to hypothesize their previous evolutionary processes by simulation, and (b) a prospective analysis of IAV to make predictions of potential mutations by simulation. What distinguishes our simulation approach from the common phylogenetic tree analysis is that we can provide more detailed information of IAV evolution by generating complete evolutionary paths that record each possible mutation step during evolution under specified temporal and geographic constraints, compared with a phylogenetic tree that shows only the phylogenetic ordering of IAV in the hierarchy of a simple tree. In addition, we can estimate the IAV sequence mutation rates from the simulated evolutionary paths produced from the retrospective simulations, and subsequently make predictions of future evolutions of IAV based on the estimated mutation rates through stochastic processes. These predictions can offer insights to virologists and public health specialists for better drug designs and public health policies. We have conducted experiments on IAV’s two internal protein segments, PB1 and PB2, and the results appear promising. We plan to continue the experiments on other IAV protein segments to further demonstrate the feasibility of our simulation approach.
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