Classification algorithms for phenotype prediction in genomics and proteomics.
Classification algorithms for phenotype prediction in genomics and proteomics.
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DOI：
10.2741/2712
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
H. Ressom;R. Varghese;Zhen Zhang;J. Xuan;R. Clarke
中科院分区：
文献类型：
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作者：
H. Ressom;R. Varghese;Zhen Zhang;J. Xuan;R. Clarke
本文概述了基于统计和机器学习的特征选择和模式分类算法及其在分子癌症分类或表型预测中的应用。特别是，本文重点介绍了使用这些计算方法分别从微阵列和质谱数据中选择基因和峰。所选择的特征被呈现给分类器以进行表型预测。
This paper gives an overview of statistical and machine learning-based feature selection and pattern classification algorithms and their application in molecular cancer classification or phenotype prediction. In particular, the paper focuses on the use of these computational methods for gene and peak selection from microarray and mass spectrometry data, respectively. The selected features are presented to a classifier for phenotype prediction.