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Comparison of Clustering Methods in Yeast Saccharomyces Cerevisiae
  • ISSN号：1674-862X
  • 期刊名称：《电子科技学刊：英文版》
  • 时间：0
  • 分类：TP311.13[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术] TS261.11[轻工技术与工程—发酵工程;轻工技术与工程—食品科学与工程]
  • 作者机构：[1]School of Life Science and Technology, University of Electronic Science and Technology of China） Chcngdu 610054, China
  • 相关基金：This work was supported by the National Natural Science Foundation of China under Grant No. 30525030, 60701015, and 60736029.
作者： Wen Wang Ni-Ni Rao Xi Chen Shang-Lei Xu[1]
关键词： 酿酒酵母, 聚类方法, 基因表达, 均值聚类, 基因芯片技术, 聚类分析, 分层聚类, 同步监测, Fuzzy c-means, hierarchical clustering, k-means, yeast saecharomyees cerevisiae.
中文摘要：

在最近的年里， microarray 技术广泛地在生物、临床的研究被使用了因为在聚类分析的几千 genes.Gene 的基因表示的同时的监视为发现一些相关基因潜在地共同调整被发现有用或在包括k工具聚类方法的 investigation.Many 下面联系了到疾病或条件，模糊c工具，并且层次聚类广泛地不在 literatures.Yet 被使用了全面比较学习是 perf

英文摘要：

In recent years, microarray technology has been widely applied in biological and clinical studies for simultaneous monitoring of gene expression in thousands of genes. Gene clustering analysis is found useful for discovering groups of correlated genes potentially co-regulated or associated to the disease or conditions under investigation. Many clustering methods including k-means, fuzzy c-means, and hierarchical clustering have been widely used in literatures. Yet no comprehensive comparative study has been performed to evaluate the effectiveness of these methods, specially, in yeast saccharomyces cerevisiae. In this paper, these three gene clustering methods are compared. Classification accuracy and CPU time cost are employed for measuring performance of these algorithms. Our results show that hierarchical clustering outperforms k-means and fuzzy c-means clustering. The analysis provides deep insight to the complicated gene clustering problem of expression profile and serves as a practical guideline for routine microarray cluster analysis of gene expression.

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期刊信息
  • 《电子科技学刊：英文版》
  • 主管单位:
  • 主办单位:电子科技大学
  • 主编：周小佳
  • 地址：成都市建设北路
  • 邮编：610054
  • 邮箱：journal@westc.edu.cn
  • 电话：028-83200028
  • 国际标准刊号：ISSN：1674-862X
  • 国内统一刊号：ISSN：51-1724/TN
  • 邮发代号:62-268
  • 获奖情况:
  • 第二届中国高校特色科技期刊奖
  • 国内外数据库收录:
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  • 被引量:6