A computational neural approach to support the discovery of gene function and classes of cancer

IEEE Transactions on Bio-medical Engineering
F Azuaje

Abstract

Advances in molecular classification of tumours may play a central role in cancer treatment. Here, a novel approach to genome expression pattern interpretation is described and applied to the recognition of B-cell malignancies as a test set. Using cDNA microarrays data generated by a previous study, a neural network model known as simplified fuzzy ARTMAP is able to identify normal and diffuse large B-cell lymphoma (DLBCL) patients. Furthermore, it discovers the distinction between patients with molecularly distinct forms of DLBCL without previous knowledge of those subtypes.

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Citations

Feb 21, 2003·Annals of the New York Academy of Sciences·Faramarz Valafar
Aug 4, 2004·Journal of Bioinformatics and Computational Biology·Stergios Papadimitriou, Spiridon D Likothanassis
Oct 9, 2007·Alimentary Pharmacology & Therapeutics·G CampisiA Carroccio
Sep 22, 2010·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Alfredo BensoGianfranco Politano
Mar 11, 2009·IEEE Transactions on Bio-medical Engineering·Hei-Chia Wang, Tian-Hsiang Huang
Sep 4, 2015·IEEE/ACM Transactions on Computational Biology and Bioinformatics·Sun-Yuan Hsieh, Yu-Chun Chou
Aug 17, 2005·Artificial Intelligence in Medicine·Jin-Hyuk Hong, Sung-Bae Cho
Jun 19, 2004·Leukemia & Lymphoma·Lucia LoniRomano Danesi
Jul 17, 2008·Comparative and Functional Genomics·Andrei DragomirAnastasios Bezerianos

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