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Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis

机译：采用综合方法掺入人工神经网络，集群分析和主要成分分析的组合方法对蛋白质组学数据的分类

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L. Lancashire; O. Schmid; H. Shah; G. Ball;
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年度 2005
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1. Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis [J] . Lancashire L, Schmid O, Shah H, Bioinformatics . 2005,第10期

机译：使用结合人工神经网络，聚类分析和主成分分析的组合方法从蛋白质组学数据对细菌物种进行分类
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3. Parsimonious classification of binary lacunarity data computed from food surface images using kernel principal component analysis and artificial neural networks [J] . Abdullah Iqbal, Nektarios A. Valous, Da-Wen Sun, Meat Science . 2011,第2期

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4. A classification of multitemporal Landsat TM data using principal component analysis and artificial neural network [C] . Chae, H.S., Kim, Geoscience and Remote Sensing, 1997. IGARSS '97. Remote Sensing - A Scientific Vision for Sustainable Development., 1997 IEEE International . 1997

机译：基于主成分分析和人工神经网络的多时相Landsat TM数据分类
5. Application of principal component analysis and artificial neural networks in the determination of filler dispersion during polymer extrusion processes. [D] . Yan, Jian. 2003

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6. Principal Component Analysis Coupled with Artificial Neural Networks—A Combined Technique Classifying Small Molecular Structures Using a Concatenated Spectral Database [O] . Steluţa Gosav, Mirela Praisler, Mihail Lucian Birsa 2011

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Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis

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