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GECCO
2003
Springer

Artificial Immune System for Classification of Gene Expression Data

12 years 2 months ago
Artificial Immune System for Classification of Gene Expression Data
DNA microarray experiments generate thousands of gene expression measurement simultaneously. Analyzing the difference of gene expression in cell and tissue samples is useful in diagnosis of disease. This paper presents an Artificial Immune System for classifying microarray-monitored data. The system evolutionarily selects important features and optimizes their weights to derive classification rules. This system was applied to two datasets of cancerous cells and tissues. The primary result found few classification rules which correctly classified all the test samples and gave some interesting implications for feature selection.
Shin Ando, Hitoshi Iba
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where GECCO
Authors Shin Ando, Hitoshi Iba
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