教師資料查詢 | 類別: 期刊論文 | 教師: 陳昆皇 KUN-HUANG CHEN (瀏覽個人網頁)

標題:Gene selection for cancer identification: a decision tree model empowered by particle swarm optimization algorithm
學年102
學期2
出版(發表)日期2014/02/07
作品名稱Gene selection for cancer identification: a decision tree model empowered by particle swarm optimization algorithm
作品名稱(其他語言)
著者K.-H. Chen; K.-J. Wang; M.-L. Tsai; K.-M. Wang; A-M. Adrian; W.-C. Cheng; T.-S. Yang; N.-C. Teng; K.-P. Tan; K.-S. Chang
單位
出版者
著錄名稱、卷期、頁數BMC Bioinformatics 15(49)
摘要Background
In the application of microarray data, how to select a small number of informative genes from thousands of genes that may contribute to the occurrence of cancers is an important issue. Many researchers use various computational intelligence methods to analyzed gene expression data.

Results
To achieve efficient gene selection from thousands of candidate genes that can contribute in identifying cancers, this study aims at developing a novel method utilizing particle swarm optimization combined with a decision tree as the classifier. This study also compares the performance of our proposed method with other well-known benchmark classification methods (support vector machine, self-organizing map, back propagation neural network, C4.5 decision tree, Naive Bayes, CART decision tree, and artificial immune recognition system) and conducts experiments on 11 gene expression cancer datasets.

Conclusion
Based on statistical analysis, our proposed method outperforms other popular classifiers for all test datasets, and is compatible to SVM for certain specific datasets. Further, the housekeeping genes with various expression patterns and tissue-specific genes are identified. These genes provide a high discrimination power on cancer classification.
關鍵字Gene expression;Cancer;Particle swarm optimization;Decision tree classifier
語言英文
ISSN1471-2105
期刊性質國外
收錄於SCI;
產學合作
通訊作者K.-H. Chen
審稿制度
國別英國
公開徵稿
出版型式,電子版
相關連結
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