Artificial Immune System for Classification of Gene Expression Data
Artificial Immune System for Classification of Gene Expression Data
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DOI：
10.1007/3-540-45110-2_92
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发表时间：
2003-07
期刊：
影响因子：
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通讯作者：
S. Ando;H. Iba
中科院分区：
文献类型：
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作者：
S. Ando;H. Iba
DNA微阵列实验同时产生数千个基因表达测量。分析细胞和组织样本中基因表达的差异有助于疾病的诊断。本文提出了一种用于微阵列监测数据分类的人工免疫系统。系统进化地选择重要特征并优化其权重以导出分类规则。该系统被应用于癌细胞和组织的两个数据集。初步结果发现，正确分类所有测试样本的分类规则很少，并给出了一些有趣的特征选择的影响。
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.