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

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 2001年 / 48卷 / 03期

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

页码：332 / 339

页数：8

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