DocumentCode :
3189006
Title :
A High performance cloud computing platform for mRNA analysis
Author :
Feng-Seng Lin ; Chia-Ping Shen ; Hsiao-Ya Sung ; Yan-Yu Lam ; Jeng-Wei Lin ; Feipei Lai
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fYear :
2013
fDate :
3-7 July 2013
Firstpage :
1510
Lastpage :
1513
Abstract :
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.
Keywords :
Internet; RNA; bioinformatics; cancer; cloud computing; genetic algorithms; human computer interaction; molecular biophysics; pattern classification; public domain software; support vector machines; Apache Hadoop design framework; GA-SVM classification; bioinformatics data; computation power; genetic algorithm; high performance cloud computing platform; mRNA benchmark cancer dataset; multiclass classification; support vector machines; two layer architecture; user-friendly Web interface; Accuracy; Bioinformatics; Biological cells; Computer architecture; Genetic algorithms; Support vector machines; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
ISSN :
1557-170X
Type :
conf
DOI :
10.1109/EMBC.2013.6609799
Filename :
6609799
Link To Document :
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