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

被引:45
作者
Azuaje, F [1 ]
机构
[1] Univ Dublin Trinity Coll, Artificial Intelligence Grp, Dublin 2, Ireland
[2] Univ Dublin Trinity Coll, Ctr Hlth Informat, Dublin 2, Ireland
关键词
bioinformatics; cancer classification; data mining; gene expression analysis; neural networks;
D O I
10.1109/10.914796
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
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.
引用
收藏
页码:332 / 339
页数:8
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