Title :
A novel algorithm for generating simulated genetic data based on K-medoids
Author :
Jianan Wu ; Chunguang Zhou ; Zhangxu Li ; Xuefei Xia ; Seng Zhang ; You Zhou
Author_Institution :
Coll. of Comput. Sci. & Technol., Jilin Univ., Changchun, China
fDate :
Oct. 30 2012-Nov. 1 2012
Abstract :
Genetic data is very important for biological research, but it is hard to be obtained by experiment. In this paper, we introduce an algorithm for generating simulated genetic data based on K-mediods. A concept of Cluster Channel is proposed in this algorithm and used to generate simulated data. The noise of origin data could be eliminated using the proposed method. The experimental results show reliability of simulated genetic data. SAM is used to analyze the simulated data and original data, and we get a conclusion that the simulated data can effectively validate differentially expressed gene detected algorithm.
Keywords :
biology; data handling; genetic algorithms; pattern clustering; K-medoids; biological research; cluster channel concept; gene detected algorithm; novel algorithm; simulated genetic data; Algorithm design and analysis; Arrays; Clustering algorithms; Gene expression; Noise; Cluster channel; Genetic data; K-medoids; Simulated genetic data;
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
DOI :
10.1109/CCIS.2012.6664360
