NDLI: Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data

Content Provider	ACM Digital Library
Author	Xu, Rui Anagnostopoulos, Georgios C. Wunsch, Donald C.
Abstract	It is crucial for cancer diagnosis and treatment to accurately identify the site of origin of a tumor. With the emergence and rapid advancement of DNA microarray technologies, constructing gene expression profiles for different cancer types has already become a promising means for cancer classification. In addition to research on binary classification such as normal versus tumor samples, which attracts numerous efforts from a variety of disciplines, the discrimination of multiple tumor types is also important. Meanwhile, the selection of genes which are relevant to a certain cancer type not only improves the performance of the classifiers, but also provides molecular insights for treatment and drug development. Here, we use Semisupervised Ellipsoid ARTMAP (ssEAM) for multiclass cancer discrimination and particle swarm optimization for informative gene selection. ssEAM is a neural network architecture rooted in Adaptive Resonance Theory and suitable for classification tasks. ssEAM features fast, stable, and finite learning and creates hyperellipsoidal clusters, inducing complex nonlinear decision boundaries. PSO is an evolutionary algorithm-based technique for global optimization. A discrete binary version of PSO is employed to indicate whether genes are chosen or not. The effectiveness of ssEAM/PSO for multiclass cancer diagnosis is demonstrated by testing it on three publicly available multiple-class cancer data sets. ssEAM/PSO achieves competitive performance on all these data sets, with results comparable to or better than those obtained by other classifiers.
Starting Page	65
Ending Page	77
Page Count	13
File Format	PDF
ISSN	15455963
DOI	10.1109/TCBB.2007.1009
Volume Number	4
Issue Number	1
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2007-01-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cancer classification, gene expression profile, semisupervised ellipsoid ARTMAP, particle swarm optimization.
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

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Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data

D.C.I.I.,"Multiclass Cancer Classification Using Semi supervised Ellipsoid ARTMAP And Particle Swarm Optimization With Gene Expression Data (2007)

D.C.I.I.,"Multiclass Cancer Classification Using Semi supervised Ellipsoid ARTMAP And Particle Swarm Optimization With Gene Expression Data (2007)

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Multiclass Cancer Classification Using Semisupervised Ellipsoid ARTMAP and Particle Swarm Optimization with Gene Expression Data

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