Bioinformatics and Computational Biology Solutions Using R and Bioconductor (eBook)

Robert Gentleman, Vincent Carey, Wolfgang Huber, Rafael Irizarry, Sandrine Dudoit (Herausgeber)

eBook Download: PDF

2005 | 2005
XIX, 474 Seiten
Springer New York (Verlag)
978-0-387-29362-2 (ISBN)

Infos

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.

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Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R.This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms:Curation and delivery of biological metadata for use in statistical modeling and interpretationStatistical analysis of high-throughput data, including machine learning and visualizationModeling and visualization of graphs and networksThe developers of the software, who are in many cases leading academic researchers, jointly authored chapters. All methods are illustrated with publicly available data, and a major section of the book is devoted to exposition of fully worked case studies.This book is more than a static collection of descriptive text, figures, and code examples that were run by the authors to produce the text; it is a dynamic document. 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.

Inhalt

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 toannotated lists of interesting genes –R. A. Irizarry

Produkt-Details

• Erscheint lt. Verlag: 29.12.2005
• Reihe/Serie: Statistics for Biology and Health
• Reihe/Serie: Statistics for Biology and Health
• Zusatzinfo: XX, 474 p. 128 illus. in color.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Medizin / Pharmazie ► Allgemeines / Lexika
• Themenwelt: Naturwissenschaften ► Biologie
• Themenwelt: Technik
• Schlagworte: Annotation • Bioinformatics • Biology • Calculus • classification • cluster analysis • Data Analysis • DNA • genes • Genome • genomics • machine learning • microarray • Processing • Protein
• ISBN-10: 0-387-29362-0 / 0387293620
• ISBN-13: 978-0-387-29362-2 / 9780387293622