The discovery of genes that are responsible for cell responses to drugs, i.e., pharmacogenes, is a key task in pharmacogenomics. In this work we propose a new approach for pharmacogenes identification integrating: i) a filter and a wrapper feature selection technique, and ii) three sources of knowledge, namely transcriptional profiles, drugs activity, and path- way interactions. We show that the integration of multiple feature selection approaches as well as of several sources of knowledge increases the accuracy of the results.

Improving biomarker discovering for chemosensitivity prediction using an integrated approach

CORDERO, Francesca;VISCONTI, ALESSIA;CALOGERO, Raffaele Adolfo
2012

Abstract

The discovery of genes that are responsible for cell responses to drugs, i.e., pharmacogenes, is a key task in pharmacogenomics. In this work we propose a new approach for pharmacogenes identification integrating: i) a filter and a wrapper feature selection technique, and ii) three sources of knowledge, namely transcriptional profiles, drugs activity, and path- way interactions. We show that the integration of multiple feature selection approaches as well as of several sources of knowledge increases the accuracy of the results.
Ninth Annual Meeting of the Bioinformatics Italian Society (BITS)
Catania
2-4 Maggio 2012
-
18
24
24
pharmacogenes discovery; feature selection; NCI60 panel; genetic algorithm
Francesca Cordero; Alessia Visconti; Raffaele A Calogero
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2318/124623
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