Bioinformatics and Computational Biology Solutions Using R and Bioconductor / Edition 1

Bioinformatics and Computational Biology Solutions Using R and Bioconductor / Edition 1

by Robert Gentleman
     
 

ISBN-10: 0387251464

ISBN-13: 9780387251462

Pub. Date: 10/28/2005

Publisher: Springer New York

Full four-color book.

Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R.

All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies.

Code underlying all of the computations that are shown is made available on a companion website,

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Overview

Full four-color book.

Some of the editors created the Bioconductor project and Robert Gentleman is one of the two originators of R.

All methods are illustrated with publicly available data, and a major section of the book is devoted to fully worked case studies.

Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.

Product Details

ISBN-13:
9780387251462
Publisher:
Springer New York
Publication date:
10/28/2005
Series:
Statistics for Biology and Health Series
Edition description:
2005
Pages:
474
Product dimensions:
6.46(w) x 9.56(h) x 1.21(d)

Related Subjects

Table of Contents

Preprocessing overview –W. Huber, R. A. Irizarry, R. Gentleman.- Preprocessing High-density Oligonucleotide Arrays –B. M. Bolstad, R. A. Irizarry, L. Gautier, Z. Wu.- Quality Assessment of Affymetrix GeneChip Data –B. M. Bolstad, F. Collin, J. Brettschneider, K. Simpson, L. Cope, R. Irizarry, T. P. Speed.- Preprocessing Two-color Spotted Arrays –Y. H. Yang and A. C. Paquet.- Cell-based assays–W. Huber and F. Hahne.- SELDI-TOF Mass Spectrometry Protein Data –X. Li, R. Gentleman, X. Lu, Q. Shi, J.D. Iglehart, L. Harris and A. Miron.- Meta-data Resources and Tools in Bioconductor–R. Gentleman, V. J. Carey, and J. Zhang .- Querying on line resources –V. J. Carey, D. Temple Lang, J. Gentry, J. Zhang and R.Gentleman.- Interactive Outputs –C. A. Smith, W. Huber and R. Gentleman.- Visualizing Data–W.Huber, X. Li and R. Gentleman.- Analysis overview–V.J. Carey and R. Gentleman.- Distance Measures in DNA Microarray Data Analysis–R. Gentleman, B. Ding, S. Dudoit, and J. Ibrahim.- Cluster Analysis of Genomic Data –K. S. Pollard and M. J. van der Laan.- Analysis of differential gene expression studies–D. Scholtens and A. von Heydebreck.- Multiple Testing Procedures: R multtest Package and Applications to Genomics –K. S. Pollard, S. Dudoit, and M. J. van der Laan.- Machine learning concepts and tools for statistical genomics–V. J. Carey.- Ensemble methods of computational inference –T. Hothorn, M. Dettling, P. Bühlmann.- Browser-Based Affymetrix Analysis and Annotation –C. A. Smith.- Introduction and motivating examples–R. Gentleman, W. Huber and V. J. Carey.- Graphs–W. Huber, R. Gentleman and V. J. Carey.-Bioconductor software for graphs –V. J. Carey, R. Gentleman, W. Huber and J. Gentry.- Case Studies using Graphs on Biological Data–R. Gentleman, D. Scholtens, B. Ding, V. J. Carey, and W. Huber.- Limma: Linear Models for Microarray Data –G. K. Smyth.- Classification with Gene Expression Data –M. Dettling.- From Cel files to annotated lists of interesting genes –R. A. Irizarry

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