Analyzing microarray gene expression data
著者
書誌事項
Analyzing microarray gene expression data
(Wiley series in probability and mathematical statistics)
Wiley-Interscience, c2004
- : cloth
大学図書館所蔵 全26件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references (p. 267-296) and indexes
内容説明・目次
内容説明
A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date.
Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including:
An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues
Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies
A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples
The latest data cleaning and normalization procedures
The uses of microarray expression data for providing important prognostic information on the outcome of disease
目次
Preface. 1. Microarrays in Gene Expression Studies.
2. Cleaning and Normalization.
3. Some Cluster Analysis Methods.
4. Clustering of Tissue Samples.
5. Screening and Clustering of Genes.
6. Discriminant Analysis.
7. Supervised Classification of Tissue Samples.
8. Linking Microarray Data with Survival Analysis.
References.
Author Index.
Subject Index.
「Nielsen BookData」 より