"RIV/00216208:11320/13:10159485!RIV14-MSM-11320___" . . "Microarrays for simultaneous measurement of redundancy of RNA species are widely used for fundamental biology research. They are also tested for their use in personalized medicine in disease diagnosis and prognosis. From the point of mathematical statistics, the invention of microarray technology in the mid-1990s allowed the simultaneous monitoring of the expression levels of thousands of genes. Microarrays for simultaneous measurement of redundancy of RNA species are used in fundamental biology as well as in medical research. Microarray may be considered as an observation of very high dimensionality equal to the number of expression levels. There arise some needs to develop new statistical methods to handle the data of such large dimensionality, especially connected to the fact of small number of observations (which is the number of arrays). Because of the small number of observations the standard asymptotic methods of multivariate statistical analysis appear to be inapplicable. The aim of the book is to familiarize the readers with statistical methods used nowadays in microarray analysis. It is addressed to everybody who is involved or is planning to be involved in statistical data analysis of microarrays, mostly to statisticians but also to biological researchers."@en . "11320" . "I" . "http://link.springer.com/book/10.1007%2F978-1-60327-337-4" . . . . "Microarrays for simultaneous measurement of redundancy of RNA species are widely used for fundamental biology research. They are also tested for their use in personalized medicine in disease diagnosis and prognosis. From the point of mathematical statistics, the invention of microarray technology in the mid-1990s allowed the simultaneous monitoring of the expression levels of thousands of genes. Microarrays for simultaneous measurement of redundancy of RNA species are used in fundamental biology as well as in medical research. Microarray may be considered as an observation of very high dimensionality equal to the number of expression levels. There arise some needs to develop new statistical methods to handle the data of such large dimensionality, especially connected to the fact of small number of observations (which is the number of arrays). Because of the small number of observations the standard asymptotic methods of multivariate statistical analysis appear to be inapplicable. The aim of the book is to familiarize the readers with statistical methods used nowadays in microarray analysis. It is addressed to everybody who is involved or is planning to be involved in statistical data analysis of microarrays, mostly to statisticians but also to biological researchers." . . . "Yakovlev, Andrei" . "Statistical Methods for Microarray Data Analysis"@en . . . . "[E0B74BEA1BC1]" . . "Statistical Methods for Microarray Data Analysis"@en . "Statistical Methods for Microarray Data Analysis" . "Klebanov, Lev" . "Galle, Daniel" . . . "22"^^ . "1"^^ . . "multiple testing procedures.; statistical test; data mining; gene expressions; Microarrays"@en . . "RIV/00216208:11320/13:10159485" . "Statistical Methods for Microarray Data Analysis" . . . . "10.1007/978-1-60327-337-4" . "107777" .