| Summary: | 碩士 === 國立交通大學 === 資訊科學與工程研究所 === 101 === Bioinformatics is the application of information technology to the management of biological data in order to increase the understanding of biological processes. The biologists use the method of feature selection to obtain the informative data in the enormous and complex data. The inheritable bi-objective genetic algorithm has been proven to have more accuracy and efficiency to solve the optimization problem in selecting a minimal number of informative features while maximizing the prediction accuracy. However, the existing implementation of the inheritable bi-objective genetic algorithm may not be scalable when it runs on highly parallel machines and it is not widely accessible to all biologists. Therefore, this study aims to improve the scalability and accessibility of the application so that it could be used in a cloud computing environment using the SaaS (Software as a Service) model.
After effectively exploiting data parallelism and thread-level parallelism of some time consuming components in the inheritable bi-objective genetic algorithm application, the application can run 5.7 times faster than before. In addition, through the implementation of a web interface, the biologists with internet access could benefit from the application of this intelligent algorithm. This thesis work has increased the potential impact of the intelligent inheritable bi-objective genetic algorithm.
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