期刊文献+

MATLAB 7.X生物信息工具箱的应用——基因表达图谱分析(4)

The Application of MATLAB Bioinformatics Toolbox——Analyzing Gene Expression Profiles(4)
原文传递
导出
摘要 基因表达图谱原则上可了解整体细胞基因表达的信息,是基因组功能分析的重要研究手段。MATLAB 7.X生物信息工具箱为基因表达谱数据的分析和处理提供了一个综合环境,通过众多统计函数和绘图函数的结合使用,过滤不合格的基因数据和噪声数据,从而对基因表达数据进行聚类分析和主成分分析,绘制相关的基因表达图谱,完成基因芯片数据表达图谱的分析,分析结果可视化程度高,图表清晰、直观。本文主要以酿酒酵母Saccharomyces cerevisiae为例,详细描述了利用MATLAB 7.X生物信息工具箱对其基因表达图谱进行分析的过程。 The gene expression profiles is an important research tool to understand the overall gene expression and functional analysis for the genome.MATLAB 7.X Bioinformatics Toolbox supplies a comprehensive platform for analyzing and disposing gene expression data.By using statistic functions and plot functions,gene expression profiles were finally gotten from microarraydata expression analyses,such as unqualified gene and noisy datas filtering analysis,gene cluster analysis,gene principal component analysis and plotting correlative gene expression profiles.Gene principal component analysis results that the most singal focus on the first two principal components,analytic result has high degree visualization and charts are in focus and visual.In this paper,the wine yeast Saccharomyces cerevisiae was used for analyzing by MATLAB 7.X bioinformatics toolbox,results showed that Bioinformatics Toolbox is a powerful tool to analyze gene expression profiles.
出处 《现代生物医学进展》 CAS 2012年第20期3938-3942,3952,共6页 Progress in Modern Biomedicine
基金 国家自然科学基金(50774102)提供资助
关键词 基因芯片 生物信息工具箱 聚类分析 主成分分析 Gene chip Cluster analysis Principal component analysis Bioinformatics Toolbox
  • 相关文献

参考文献15

  • 1唐榕,应康,陈宣茂,孙朝辉,石军,吴超群,黄燕,刘建平,李瑶,谢毅,毛裕民.用基因芯片的方法对人酪蛋白激酶CK1γ1基因进行表达谱和聚类分析[J].复旦学报(自然科学版),2000,39(6):618-622. 被引量:3
  • 2Auer H,Newsom DL,Kornacker K.Expression Profiling Using Affy-metrix GeneChip Microarrays[J].Methods Mol Biol.2009,509:35-46.
  • 3Luzzi VI,Holtschlag V,Watson MA.Gene expression profiling of pri-mary tumor cell populations using laser capture microdissection,RNAtranscript amplification,and GeneChip microarrays[J].Methods MolBiol.2005,293:187-207.
  • 4Zhu T.Global analysis of gene expression using GeneChip microarra-ys[J].Curr Opin Plant Biol.,2003,6(5):418-425.
  • 5Greenberg S A.DNA microarray gene expression analysis technologyand its application to neurological disorders[J].Neurology.2001,57(5):755-761.
  • 6杨春梅,万柏坤,高晓峰.基因聚类分析中数据预处理方式和相似度的选择[J].自然科学进展,2006,16(3):293-299. 被引量:9
  • 7Wesolowski R,Ramaswamy B.Gene expression profiling:changing f-ace of breast cancer classification and management[J].Gene Expr,2011,15(3):105-115.
  • 8Reis-Filho JS,Pusztai L.Gene expression profiling in breast cancer:classification,prognostication,and prediction[J].Lancet,2011,378(9805):1812-1823.
  • 9De Nadal E,Ammerer G,Posas F.Controlling gene expression in resp-onse to stress[J].Nat Rev Genet,2011,12(12):833-845.
  • 10DeRisi J L,Iyer V R,Brown P O.Exploring the metabolic and genet-ic control of gene expression on a genomic scale[J].Science,1997,278(5338):680-686.

二级参考文献57

  • 1YANG Chunmei,WAN Baikun,GAO Xiaofeng.Selections of data preprocessing methods and similarity metrics for gene cluster analysis[J].Progress in Natural Science:Materials International,2006,16(6):607-613. 被引量:4
  • 2[1]Johansson,(O).,et al.2003.Identification of functional clusters of transcription factor binding motifs in genome sequences:the MSCAN algorithm.Bioinformatics 19:i169-176.
  • 3[2]van Helden,J.,et al.1998.Extracting regulatory sites from the upstream region of yeast genes by computational analysis of oligonucleotide frequencies.J.Mol.Biol.281:827-842.
  • 4[3]Hertz,G.Z.and Stormo,G.D.1999.Identifying DNA and protein patterns with statistically significant alignments of multiple sequences.Bioinformatics 15:563-577.
  • 5[4]Hughes,J.D.,et al.2000.Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae.J.Mol.Biol.296:1205-1214.
  • 6[5]Jensen,S.T.,et al.2004.Computational discovery of gene regulatory binding motifs:a Bayesian perspective.Statist.Sci.19:188-204.
  • 7[6]Sinha,S.,et al.2004.PhyME:a probabilistic algorithm for finding motifs in sets of orthologous sequences.BMC Bioinformatics 5:170.
  • 8[7]Roth,F.P.,et al.1998.Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation.Nat.Biotechnol.16:939-945.
  • 9[8]Tavazoie,S.,et al.1999.Systematic determination of genetic network architecture.Nat.Genet.22:281-285.
  • 10[9]Segal,E.,et al.2003.Module networks:identifying regulatory modules and their condition-specific regulators from gene expression data.Nat.Genet.34:166-176.

共引文献23

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部