Multiclass cancer classification using a feature subset-based ensemble from microRNA expression profiles
Cancer classification has been a crucial topic of research in cancer treatment. In the last decade, messenger RNA (mRNA) expression profiles have been widely used to classify different types of cancers. With the discovery of a new class of small non-coding RNAs; known as microRNAs (miRNAs), various studies have shown that the expression patterns of miRNA can also accurately classify human cancers. Therefore, there is a great demand for the development of machine learning approaches to accurately classify various types of cancers using miRNA expression data.
Source: Computers in Biology and Medicine - Category: Bioinformatics Authors: Yongjun Piao, Minghao Piao, Keun Ho Ryu Source Type: research
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