Artificial Immune Networks as a Paradigm for Classification and Profiling of Gene Expression Data
The paper introduces a methodology of using artificial immune network systems (AINS) for classification and in particular—classification of gene expression data. AINS are computational models that adopt principles from biological immune systems. Two types of AINS are explored in the paper. For an illustrative case study we have used publicly available gene expression data of two types of Lymphoma—DLBCL and FL, and also diffuse large B-cell lymphoma (DLBCL) patient survival data after chemotherapy (Shipp et al., 2002). The results demonstrate the applicability of the AINS as classifiers in biomedical decision support systems.
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Document Type: Research Article
Publication date: December 1, 2005
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