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One of today's most important scientific research topics is discovering the genetic links between cancers. This paper contains the results of a comparison of three different cancers (breast, colon, and lung) based on the results of feature selection techniques on a data set created from DNA micro array data consisting of samples from all three cancers. The data was run through a set of eighteen feature...
Microarray datasets comprise a large number of gene expression values and a relatively small number of samples. Feature selection algorithms are very useful in these situations in order to find a compact subset of informative features. We propose a redundancy control method for algorithms in the recently proposed SPEC family of spectral-based feature selection algorithms. This method is applied to...
Identification of a small set of discriminative genes is a crucial step for effective prediction of disease or patient survival based on microarray gene expression data. Previous approaches to this problem are mainly based on analyzing differential gene expression data. In this work, an additional step is introduced to take advantage of prior knowledge about the relation of genes and a disease. In...
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