Multiclass cancer classification using a feature subset-based ensemble from microRNA expression profiles

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• 作者：Yongjun Piao^a ; ^{pyz@dblab.chungbuk.ac.kr} ; Minghao Piao^b ; ^{myunghopark@gmail.com} ; Keun Ho Ryu^a ; ^{khryu@dblab.chungbuk.ac.kr}
• 关键词：Cancer classification ; Data mining ; Ensemble learning ; miRNA expression
• 刊名：Computers in Biology and Medicine
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：80
• 期：Complete
• 页码：39-44
• 全文大小：626 K
• 卷排序：80

文摘

Multiclass cancer classification problem was approached using miRNA expression profiles. A novel feature subset-based ensemble method with high prediction accuracy was developed and made publicly available online. Supports both array-based and NGS-based miRNA expression data. Opens a new possibility to improve decision making in cancer research.