Statistical Analysis Of Gene Expression Microarray Data

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Statistical Analysis Of Gene Expression Microarray Data

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Author : Terry Speed
language : en
Publisher: CRC Press
Release Date : 2003-03-26

Statistical Analysis Of Gene Expression Microarray Data written by Terry Speed and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-03-26 with Mathematics categories.

Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists, geneticists, and computer scientists as well as statisticians all need an accessible, systematic treatment of the techniques used for analyzing the vast amounts of data generated by large-scale gene expression studies

Microarray Data

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Author : Shailaja R. Deshmukh
language : en
Publisher: Alpha Science International, Limited
Release Date : 2007

Microarray Data written by Shailaja R. Deshmukh and has been published by Alpha Science International, Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Business & Economics categories.

Functional Genomics, a branch of bioinformatics, is essentially an interdisciplinary subject in which biologists, statisticians and computer experts interact to analyze the microarray data. This book caters to the needs of all the three disciplines. For biologists and computer scientists, it explains concepts of statistics and statistical inference. For Biologists and Statisticians, it provides annotated R programs to analyze microarray data. For Statisticians and Computer scientists, it explains basics of biology relevant to microarray experiment. Thus, the book will be useful to scientists from all the three disciplines, with not much knowledge of other disciplines, to analyze microarray data and interpret the results.

Statistical Analysis Of Gene Expression Data From Dna Microarrays Based On Partial Least Squares And Related Dimension Reduction Methods

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Author : Danh V. Nguyen (Ph. D. in statistics)
language : en
Publisher:
Release Date : 2000

Statistical Analysis Of Gene Expression Data From Dna Microarrays Based On Partial Least Squares And Related Dimension Reduction Methods written by Danh V. Nguyen (Ph. D. in statistics) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with categories.

The Analysis Of Gene Expression Data

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Author : Giovanni Parmigiani
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-04-08

The Analysis Of Gene Expression Data written by Giovanni Parmigiani and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-04-08 with Medical categories.

This book presents practical approaches for the analysis of data from gene expression micro-arrays. It describes the conceptual and methodological underpinning for a statistical tool and its implementation in software. The book includes coverage of various packages that are part of the Bioconductor project and several related R tools. The materials presented cover a range of software tools designed for varied audiences.

Analysis Of Microarray Gene Expression Data

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Author : Mei-Ling Ting Lee
language : en
Publisher: Springer Science & Business Media
Release Date : 2004-04-30

Analysis Of Microarray Gene Expression Data written by Mei-Ling Ting Lee and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-30 with Mathematics categories.

After genomic sequencing, microarray technology has emerged as a widely used platform for genomic studies in the life sciences. Microarray technology provides a systematic way to survey DNA and RNA variation. With the abundance of data produced from microarray studies, however, the ultimate impact of the studies on biology will depend heavily on data mining and statistical analysis. The contribution of this book is to provide readers with an integrated presentation of various topics on analyzing microarray data.

Statistical Analysis Of Microarray Data Topics In Gene Expression

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Author : Xin Victoria Wang
language : en
Publisher:
Release Date : 2009

Statistical Analysis Of Microarray Data Topics In Gene Expression written by Xin Victoria Wang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.

Methods For Incorporating Biological Information Into The Statistical Analysis Of Gene Expression Microarray Data

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Author : Debbie Leader
language : en
Publisher:
Release Date : 2009

Methods For Incorporating Biological Information Into The Statistical Analysis Of Gene Expression Microarray Data written by Debbie Leader and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Bioinformatics categories.

Microarray technology has made it possible for researchers to simultaneously measure the expression levels of tens of thousands of genes. It is believed that most human diseases and biological phenomena occur through the interaction of groups of genes that are functionally related. To investigate the feasibility of incorporating functional information and/or constraints (based on biological and technical needs) into the classification process two approaches were examined in this thesis. The first of these approaches investigated the effect of incorporating a pre-filter into the gene selection step of the classifier construction process. Both simulated and real microarray datasets were used to assess the utility of this approach. The pre-filter was based on an early method for determining if a gene had undergone a biologically relevant level of differential expression between two classes. The genes retained by the pre-filter were ranked using one of five standard statistical ranking methods and the most highly ranked were used to construct a predictive classifier. To generate the simulated data a selection of different parametric and non-parametric techniques were employed. The results from these analyses showed that when the constraints that the pre-filter contains were placed on the classification analysis, the predictive performance of the classifiers were similar to when the pre-filter was not used. The second approach explored the feasibility of incorporating sets of functionally related genes into the classification process. Three publicly available datasets obtained from studies into breast cancer were used to assess the utility of this approach. A summary of each gene-set was derived by reducing the dimensionality of each gene-set via the use of Principal Co-ordinates Analysis. The reduced gene-sets were then ranked based on their ability to distinguish between the two classes (via Hotelling's T2) and those most highly ranked were used to construct a classifier via logistic regression. The results from the analyses undertaken for this approach showed that it was possible to incorporate function information into the classification process whilst maintaining an equivalent (if not higher) level of predictive performance, as well as improving the biological interpretability of the classifier.

Statistical Analysis Using Microarray Gene Expression Data

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Author : Xiaohong Huang
language : en
Publisher:
Release Date : 2004

Statistical Analysis Using Microarray Gene Expression Data written by Xiaohong Huang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.

Analyzing Microarray Gene Expression Data

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Author : Geoffrey J. McLachlan
language : en
Publisher: John Wiley & Sons
Release Date : 2005-02-18

Analyzing Microarray Gene Expression Data written by Geoffrey J. McLachlan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-18 with Mathematics categories.

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

Statistical Methods For Microarray Data Analysis

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Author : Andrei Y. Yakovlev
language : en
Publisher: Humana Press
Release Date : 2013-02-06

Statistical Methods For Microarray Data Analysis written by Andrei Y. Yakovlev and has been published by Humana Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-06 with Medical categories.

Microarrays for simultaneous measurement of redundancy of RNA species are used in fundamental biology as well as in medical research. Statistically,a microarray may be considered as an observation of very high dimensionality equal to the number of expression levels measured on it. In Statistical Methods for Microarray Data Analysis: Methods and Protocols, expert researchers in the field detail many methods and techniques used to study microarrays, guiding the reader from microarray technology to statistical problems of specific multivariate data analysis. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Statistical Methods for Microarray Data Analysis: Methods and Protocols aids scientists in continuing to study microarrays and the most current statistical methods.