Informative Gene Selection Method in Tumor Classification
Informative Gene Selection Method in Tumor Classification
复制标题
肿瘤分类中的信息基因选择方法
DOI：
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发表时间：
2004
期刊：
影响因子：
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通讯作者：
Jong Hoon Park
中科院分区：
文献类型：
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作者：
Hyosoo Lee;Jong Hoon Park
基因表达谱可以提供比形态学更多的信息，并提供基于形态学的肿瘤分类系统的替代方案。信息性基因选择是发现能够区分肿瘤类型的基因亚群，并且可能有明确的生物学解释。基因选择是基于基因表达的肿瘤分类的一个基本问题。在本报告中，说明了选择信息基因的技术，并介绍了监督剃须作为一种基因选择方法来代替聚类算法。监督剃须算法虽然是一种聚类算法，但在基因选择和分类方面表现出良好的性能。几乎选定的基因都与白血病有关。分析了27例急性淋巴细胞白血病和11例髓系白血病中3051个基因的表达谱。通过这些例子，监督剃须方法已被证明产生生物学上重要的基因，而不仅仅是分类的准确性。在本报告中，支持向量机也被证明是一种可行的基于基因表达的分类方法。
Gene expression profiles may offer more information than morphology and provide an alternative to morphology- based tumor classification systems. Informative gene selection is finding gene subsets that are able to discriminate between tumor types, and may have clear biological interpretation. Gene selection is a fundamental issue in gene expression based tumor classification. In this report, techniques for selecting informative genes are illustrated and supervised shaving introduced as a gene selection method in the place of a clustering algorithm. The supervised shaving method showed good performance in gene selection and classification, even though it is a clustering algorithm. Almost selected genes are related to leukemia disease. The expression profiles of 3051 genes were analyzed in 27 acute lymphoblastic leukemia and 11 myeloid leukemia samples. Through these examples, the supervised shaving method has been shown to produce biologically significant genes of more than accuracy of classification. In this report, SVM has also been shown to be a practicable method for gene expression-based classification.