Towards a Classification Approach using Meta-Biclustering: Impact of Discretization in the Analysis of Expression Time Series

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doi doi:10.2390/biecoll-jib-2012-207
submission July 07, 2012
published July 24, 2012
NCBI PubMed PubMed ID 22829578

André Valério Carreiro, Artur J. Ferreira, Mário A. T. Figueiredo and Sara Cordeiro Madeira

Correspondence should be addressed to:
Sara Madeira
Instituto Superior Técnico, Technical University of Lisbon, Portugal and Knowledge Discovery and Bioinformatics (KDBIO) group, INESC-ID, Lisbon, Portugal
tp.ltu.tsi@nullariedam.aras


Abstract

Biclustering has been recognized as a remarkably effective method for discovering local temporal expression patterns and unraveling potential regulatory mechanisms, essential to understanding complex biomedical processes, such as disease progression and drug response. In this work, we propose a classification approach based on meta-biclusters (a set of similar biclusters) applied to prognostic prediction. We use real clinical expression time series to predict the response of patients with multiple sclerosis to treatment with Interferon-!. As compared to previous approaches, the main advantages of this strategy are the interpretability of the results and the reduction of data dimensionality, due to biclustering. This would allow the identification of the genes and time points which are most promising for explaining different types of response profiles, according to clinical knowledge. We assess the impact of different unsupervised and supervised discretization techniques on the classification accuracy. The experimental results show that, in many cases, the use of these discretization methods improves the classification accuracy, as compared to the use of the original features.

Reference

André Valério Carreiro, Artur J. Ferreira, Mário A. T. Figueiredo and Sara Cordeiro Madeira. Towards a Classification Approach using Meta-Biclustering: Impact of Discretization in the Analysis of Expression Time Series. Journal of Integrative Bioinformatics, 9(3):207, 2012. Online Journal: http://journal.imbio.de/index.php?paper_id=207
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