CNS Tumor Prediction Using Gene Expression Data Part II

A. Islam, K. Iftekharuddin, E. George, D. Russomanno
{"title":"CNS Tumor Prediction Using Gene Expression Data Part II","authors":"A. Islam, K. Iftekharuddin, E. George, D. Russomanno","doi":"10.4018/978-1-59904-849-9.CH047","DOIUrl":null,"url":null,"abstract":"In this chapter, we propose a novel algorithm for characterizing a variety of CNS tumors. The proposed algorithm is illustrated with an analysis of an Affymetrix gene expression data from CNS tumor samples (Pomeroy et al., 2002). As discussed in the previous chapter entitled: CNS Tumor Prediction Using Gene Expression Data Part I, we used an ANOVA model to normalize the microarray gene expression measurements. In this chapter, we introduce a systemic way of building tumor prototypes to facilitate automatic prediction of CNS tumors.","PeriodicalId":320314,"journal":{"name":"Encyclopedia of Artificial Intelligence","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Encyclopedia of Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-59904-849-9.CH047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

In this chapter, we propose a novel algorithm for characterizing a variety of CNS tumors. The proposed algorithm is illustrated with an analysis of an Affymetrix gene expression data from CNS tumor samples (Pomeroy et al., 2002). As discussed in the previous chapter entitled: CNS Tumor Prediction Using Gene Expression Data Part I, we used an ANOVA model to normalize the microarray gene expression measurements. In this chapter, we introduce a systemic way of building tumor prototypes to facilitate automatic prediction of CNS tumors.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
利用基因表达数据预测中枢神经系统肿瘤(二)
在本章中,我们提出了一种新的算法来表征各种中枢神经系统肿瘤。通过对来自中枢神经系统肿瘤样本的Affymetrix基因表达数据的分析(Pomeroy et al., 2002)说明了所提出的算法。正如前一章所讨论的:利用基因表达数据预测中枢神经系统肿瘤第一部分,我们使用方差分析模型来标准化微阵列基因表达测量。在本章中,我们介绍了一种系统构建肿瘤原型的方法,以促进中枢神经系统肿瘤的自动预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Emerging Applications in Immersive Technologies Knowledge-Based Systems RBF Networks for Power System Topology Verification Association Rule Mining "Narrative" Information Problems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1