alysis of Multiply Myeloma Gene Expression Profile
Quanjin Liu · 2004
abstract order to extract knowledge for tissue classification from the tumour gene expression profiles, the authors analyzed the gene expression profile of multiply myeloma, and introduced an approach for extracting rules to distinguish different tissue types using statistical method and machine learning approaches. Correlation coefficients of genes with regard to tissue types were used as the criterions for their contribution to classification, and artificial neural networks were employed for feature subset selection. Identified by decision tree algorithm, three classification rules were discovered in the authors experiment, which can distinguish all the tissue types without error.