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2016 | OriginalPaper | Buchkapitel

Gene Priorization for Tumor Classification Using an Embedded Method

verfasst von : Jose M. Cadenas, M. Carmen Garrido, Raquel Martínez, David Pelta, Piero P. Bonissone

Erschienen in: Computational Intelligence

Verlag: Springer International Publishing

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Abstract

The application of microarray technology to the diagnosis of cancer has been a challenge for computational techniques because the datasets obtained have high dimension and a few examples. In this paper two computational techniques are applied to tumor datasets in order to carry out the task of diagnosis of cancer (classification task) and identifying the most promising candidates among large list of genes (gene prioritization). Both techniques obtain good classification results but only one provides a ranking of genes as additional information and thus, more interpretable models, being more suitable for jointly addressing both tasks.

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Metadaten
Titel
Gene Priorization for Tumor Classification Using an Embedded Method
verfasst von
Jose M. Cadenas
M. Carmen Garrido
Raquel Martínez
David Pelta
Piero P. Bonissone
Copyright-Jahr
2016
Verlag
Springer International Publishing
DOI
https://doi.org/10.1007/978-3-319-23392-5_20