Data mining techniques for the identification of genes with expression levels related to breast cancer prognosis

Gabriele Giarratana; Marco Pizzera; Marco Masseroli; Enzo Medico; Pier Luca Lanzi

doi:10.1109/BIBE.2009.37

Data mining techniques for the identification of genes with expression levels related to breast cancer prognosis

Gabriele Giarratana, Marco Pizzera, Marco Masseroli, Enzo Medico, Pier Luca Lanzi

Istituto Oncologico Candiolo

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Providing clinical predictions for cancer patients by analyzing their genetic make-up is a difficult and very important issue. With the goal of identifying genes more correlated with the prognosis of breast cancer, we used data mining techniques to study the gene expression values of breast cancer patients with known clinical outcome. Focus of our work was the creation of a classification model to be used in the clinical practice to support therapy prescription. We randomly subdivided a gene expression dataset of 311 samples into a training set to learn the model and a test set to validate the model and assess its performance. We evaluated several learning algorithms in their not weighted and weighted form, which we defined to take into account the different clinical importance of false positive and false negative classifications. Based on our results, these last, especially when used in their combined form, appear to provide better results.

Original language	English
Title of host publication	Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
Pages	295-300
Number of pages	6
DOIs	https://doi.org/10.1109/BIBE.2009.37
Publication status	Published - 2009
Event	2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009 - Taichung, Taiwan, Province of China Duration: Jun 22 2009 → Jun 24 2009

Other

Other	2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009
Country/Territory	Taiwan, Province of China
City	Taichung
Period	6/22/09 → 6/24/09

Keywords

Breast cancer prognosis
Data mining
Gene expression

ASJC Scopus subject areas

Information Systems
Biomedical Engineering
Health Informatics

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10.1109/BIBE.2009.37

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Data mining techniques for the identification of genes with expression levels related to breast cancer prognosis. / Giarratana, Gabriele; Pizzera, Marco; Masseroli, Marco et al.

Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009. 2009. p. 295-300 5211265.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Giarratana, G, Pizzera, M, Masseroli, M, Medico, E & Lanzi, PL 2009, Data mining techniques for the identification of genes with expression levels related to breast cancer prognosis. in Proceedings of the 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009., 5211265, pp. 295-300, 2009 9th IEEE International Conference on Bioinformatics and BioEngineering, BIBE 2009, Taichung, Taiwan, Province of China, 6/22/09. https://doi.org/10.1109/BIBE.2009.37

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Data mining techniques for the identification of genes with expression levels related to breast cancer prognosis

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Keywords

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