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Statistical methods for microarray data analysis : methods and protocols / edited by Andrei Y. Yakovlev, Lev Klebanov, Daniel Gaile.

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Language:
English.
Publication date:
2013
Imprint:
New York : Humana Press : Springer, c2013.
Format:
  • Book
  • xi, 212 p. : ill. ; 26 cm.
Bibliography:
Includes bibliographical references and index.
Contents:
  • What statisticians should know about microarray gene expression technology / Stephen Welle
  • Where statistics and molecular microarray experiments biology meet / Diana M. Kelmansky
  • Multiple hypothesis testing : a methodological overview / Anthony Almudevar
  • Gene selection with the [delta]-sequence method / Xing Qiu and Lev Klebanov
  • Using of normalizations for gene expression analysis / Peter Bubeliny
  • Constructing multivariate prognostic gene signatures with censored survival data / Derick R. Peterson
  • Clustering of gene expression data via normal mixture models / G.J. McLachlan ... [et al.]
  • Network-based analysis of multivariate gene expression data / Wei Zhi ... [et al.]
  • Genomic outlier detection in high-throughput data analysis / Debashis Ghosh
  • Impact of experimental noise and annotation imprecision on data quality in microarray experiments / Andreas Scherer, Manhong Dai, and Fan Meng
  • Aggregation effect in microarray data analysis / Linlin Chen, Anthony Almudevar, and Lev Klebanov
  • Test for normality of the gene expression data / Bobosharif Shokirov.
Contributor:
Yakovlev, Andrej Yu., 1944-
Klebanov, L. B. (Lev Borisovich), 1946-
Gaile, Daniel, 1968-
Series:
Methods in molecular biology, 1064-3745 ; 972
Springer protocols
Methods in molecular biology (Clifton, N.J.) ; v. 972.
Springer protocols (Series)
Subjects:
ISBN:
9781603273367
1603273360

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