Literature DB >> 11327501

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

F Azuaje1.   

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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Year:  2001        PMID: 11327501     DOI: 10.1109/10.914796

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  2 in total

1.  Som-based class discovery exploring the ICA-reduced features of microarray expression profiles.

Authors:  Andrei Dragomir; Seferina Mavroudi; Anastasios Bezerianos
Journal:  Comp Funct Genomics       Date:  2004

2.  Genomic data sampling and its effect on classification performance assessment.

Authors:  Francisco Azuaje
Journal:  BMC Bioinformatics       Date:  2003-01-28       Impact factor: 3.169

  2 in total

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