https://scholars.lib.ntu.edu.tw/handle/123456789/484397
標題: | A High performance cloud computing platform for mRNA analysis | 作者: | Lin, F.-S. Shen, C.-P. Sung, H.-Y. Lam, Y.-Y. Lin, J.-W. FEI-PEI LAI |
公開日期: | 2013 | 起(迄)頁: | 1510-1513 | 來源出版物: | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | 摘要: | Multiclass classification is an important technique to many complex bioinformatics problems. However, their performance is limited by the computation power. Based on the Apache Hadoop design framework, this study proposes a two layer architecture that exploits the inherent parallelism of GA-SVM classification to speed up the work. The performance evaluations on an mRNA benchmark cancer dataset have reduced 86.55% features and raised accuracy from 97.53% to 98.03%. With a user-friendly web interface, the system provides researchers an easy way to investigate the unrevealed secrets in the fast-growing repository of bioinformatics data. ? 2013 IEEE. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/484397 | DOI: | 10.1109/EMBC.2013.6609799 | SDG/關鍵字: | Bioinformatics data; Cloud computing platforms; Computation power; Design frameworks; Inherent parallelism; Layer architectures; Multi-class classification; Web interface; Bioinformatics; Computer software; Computer aided diagnosis; messenger RNA; algorithm; biology; genetics; human; procedures; theoretical model; time; Algorithms; Computational Biology; Humans; Models, Theoretical; RNA, Messenger; Time Factors |
顯示於: | 生醫電子與資訊學研究所 |
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