Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data

机译：遗传算法和构造性神经网络在微阵列癌症数据分析中的应用

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BackgroundExtracting relevant information from microarray data is a very complex task due to the characteristics of the data sets, as they comprise a large number of features while few samples are generally available. In this sense, feature selection is a very important aspect of the analysis helping in the tasks of identifying relevant genes and also for maximizing predictive information.

机译：背景技术由于数据集的特征，从微阵列数据中提取相关信息是一项非常复杂的任务，因为它们具有大量特征，而通常很少有样品可用。从这个意义上讲，特征选择是分析中非常重要的方面，有助于完成相关基因的识别任务，并有助于最大化预测信息。

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期刊名称 Theoretical Biology Medical Modelling
作者
Rafael Marcos Luque-Baena; Daniel Urda; Jose Luis Subirats; Leonardo Franco; Jose M Jerez;
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作者单位

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年(卷),期 2014(11),Suppl 1
年度 2014
页码 S7
总页数 18
原文格式 PDF
正文语种
中图分类生物学;
关键词
Microarray Genetic algorithms Constructive neural networks Feature Selection;

机译：芯片;遗传算法;建设性神经网络;特征选择;

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专利

1. Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data [J] . Rafael Marcos Luque-Baena, Daniel Urda, Jose Luis Subirats, Theoretical Biology and Medical Modelling . 2014,第SUPPLEMENTa1期

机译：遗传算法和构造性神经网络在微阵列癌症数据分析中的应用
2. O-22 A novel Artificial Neural Network based algorithm to analyse the interaction patterns existing in gene microarrays: An application to breast cancer genomic data [J] . Christophe Lemetre, Lee James Lancashire, Graham Roy Ball European Journal of Cancer Supplements . 2010,第6期

机译：O-22一种新颖的基于人工神经网络的算法，用于分析基因微阵列中存在的相互作用模式：在乳腺癌基因组数据中的应用
3. O-22 A novel Artificial Neural Network based algorithm to analyse the interaction patterns existing in gene microarrays: An application to breast cancer genomic data [J] . Christophe Lemetre, Lee James Lancashire, Graham Roy Ball European Journal of Cancer Supplements . 2010,第6期

机译：O-22一种新颖的基于人工神经网络的算法，用于分析基因微阵列中存在的相互作用模式：在乳腺癌基因组数据中的应用
4. cDNA Microarray Data Based Classification of Cancers Using Neural Networks and Genetic Algorithms [C] . Nanotechnology conference and trade show . 2003

机译：基于cDNA微阵列基于神经网络和遗传算法的癌症分类
5. Feature selection of microarray data using genetic algorithms and artificial neural networks. [D] . Yacci, Paul. 2009

机译：使用遗传算法和人工神经网络对微阵列数据进行特征选择。
6. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency [O] . Hsiang-Yuan Yeh, Shih-Wu Cheng, Yu-Chun Lin, 2009

机译：根据转录因子分析和条件独立性从微阵列数据中识别出前列腺癌中重要的基因调控网络
7. Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data [O] . Rafael Luque-Baena, Daniel Urda, Jose Subirats, 2014

机译：遗传算法和构造性神经网络在微阵列癌症数据分析中的应用
8. Hierarchical Neural Network Based Data Processing System for Ground- Penetrating Radar. An End of Year Report for CH/1049/6: Application of Neural Networks Coupled With Genetic Algorithms to Optimize Soil Cleanup Operations in Cold Climates [R] . Sullivan, J. M. 1997

机译：基于分层神经网络的探地雷达数据处理系统。 CH / 1049/6的年终报告：神经网络与遗传算法相结合的应用，以优化寒冷气候下的土壤清理作业

Application of genetic algorithms and constructive neural networks for the analysis of microarray cancer data

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