A feature selection method based on multiple kernel learning with expression profiles of different types

Abstract

With the development of high-throughput technology, the researchers can acquire large number of expression data with different types from several public databases. Because most of these data have small number of samples and hundreds or thousands features, how to extract informative features from expression data effectively and robustly using feature… (More)
DOI: 10.1186/s13040-017-0124-x

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