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Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Buch von Robert Gentleman (u. a.)
Sprache: Englisch

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Beschreibung
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 interpretation

Statistical analysis of high-throughput data, including machine learning and visualization

Modeling and visualization of graphs and networks

The 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.
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 interpretation

Statistical analysis of high-throughput data, including machine learning and visualization

Modeling and visualization of graphs and networks

The 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.
Zusammenfassung

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. 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 interpretation

statistical analysis of high-throughput data, including machine learning and visualization,

modeling and visualization of graphs and networks.

Inhaltsverzeichnis
Preprocessing data from genomic experiments.- Preprocessing Overview.- Preprocessing High-density Oligonucleotide Arrays.- Quality Assessment of Affymetrix GeneChip Data.- Preprocessing Two-Color Spotted Arrays.- Cell-Based Assays.- SELDI-TOF Mass Spectrometry Protein Data.- Meta-data: biological annotation and visualization.- Meta-data Resources and Tools in Bioconductor.- Querying On-line Resources.- Interactive Outputs.- Visualizing Data.- Statistical analysis for genomic experiments.- Analysis Overview.- Distance Measures in DNA Microarray Data Analysis.- Cluster Analysis of Genomic Data.- Analysis of Differential Gene Expression Studies.- Multiple Testing Procedures: the multtest Package and Applications to Genomics.- Machine Learning Concepts and Tools for Statistical Genomics.- Ensemble Methods of Computational Inference.- Browser-based Affymetrix Analysis and Annotation.- Graphs and networks.- and Motivating Examples.- Graphs.- Bioconductor Software for Graphs.- Case Studies Using Graphs on Biological Data.- Case studies.- limma: Linear Models for Microarray Data.- Classification with Gene Expression Data.- From CEL Files to Annotated Lists of Interesting Genes.
Details
Erscheinungsjahr: 2005
Fachbereich: Allgemeines
Genre: Biologie
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 496
Reihe: Statistics for Biology and Health
Inhalt: xix
474 S.
ISBN-13: 9780387251462
ISBN-10: 0387251464
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Redaktion: Gentleman, Robert
Carey, Vincent
Dudoit, Sandrine
Irizarry, Rafael
Huber, Wolfgang
Herausgeber: Robert Gentleman/Vincent Carey/Wolfgang Huber et al
Auflage: 2005
Hersteller: Springer New York
Springer US, New York, N.Y.
Statistics for Biology and Health
Maße: 241 x 160 x 35 mm
Von/Mit: Robert Gentleman (u. a.)
Erscheinungsdatum: 31.08.2005
Gewicht: 0,995 kg
preigu-id: 102300156
Zusammenfassung

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. 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 interpretation

statistical analysis of high-throughput data, including machine learning and visualization,

modeling and visualization of graphs and networks.

Inhaltsverzeichnis
Preprocessing data from genomic experiments.- Preprocessing Overview.- Preprocessing High-density Oligonucleotide Arrays.- Quality Assessment of Affymetrix GeneChip Data.- Preprocessing Two-Color Spotted Arrays.- Cell-Based Assays.- SELDI-TOF Mass Spectrometry Protein Data.- Meta-data: biological annotation and visualization.- Meta-data Resources and Tools in Bioconductor.- Querying On-line Resources.- Interactive Outputs.- Visualizing Data.- Statistical analysis for genomic experiments.- Analysis Overview.- Distance Measures in DNA Microarray Data Analysis.- Cluster Analysis of Genomic Data.- Analysis of Differential Gene Expression Studies.- Multiple Testing Procedures: the multtest Package and Applications to Genomics.- Machine Learning Concepts and Tools for Statistical Genomics.- Ensemble Methods of Computational Inference.- Browser-based Affymetrix Analysis and Annotation.- Graphs and networks.- and Motivating Examples.- Graphs.- Bioconductor Software for Graphs.- Case Studies Using Graphs on Biological Data.- Case studies.- limma: Linear Models for Microarray Data.- Classification with Gene Expression Data.- From CEL Files to Annotated Lists of Interesting Genes.
Details
Erscheinungsjahr: 2005
Fachbereich: Allgemeines
Genre: Biologie
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Seiten: 496
Reihe: Statistics for Biology and Health
Inhalt: xix
474 S.
ISBN-13: 9780387251462
ISBN-10: 0387251464
Sprache: Englisch
Ausstattung / Beilage: HC runder Rücken kaschiert
Einband: Gebunden
Redaktion: Gentleman, Robert
Carey, Vincent
Dudoit, Sandrine
Irizarry, Rafael
Huber, Wolfgang
Herausgeber: Robert Gentleman/Vincent Carey/Wolfgang Huber et al
Auflage: 2005
Hersteller: Springer New York
Springer US, New York, N.Y.
Statistics for Biology and Health
Maße: 241 x 160 x 35 mm
Von/Mit: Robert Gentleman (u. a.)
Erscheinungsdatum: 31.08.2005
Gewicht: 0,995 kg
preigu-id: 102300156
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