| Description |
1 online resource (x, 313 pages) : illustrations (some color) |
| Series |
Methods in molecular biology, 1940-6029 ; 1362 |
|
Springer protocols |
|
Methods in molecular biology (Clifton, N.J.) ; v. 1362. 1064-3745
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Springer protocols (Series)
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| Contents |
Introduction to proteomics technologies / Christof Lenz and Hassan Dihazi -- Topics in study design and analysis for multistage clinical proteomics studies / Irene Sui Lan Zeng -- Preprocessing and analysis of LC-MS-based proteomic data / Tsung-Heng Tsai, Minkun Wang, and Habtom W. Ressom -- Normalization of reverse phase protein microarray data : choosing the best normalization analyte / Antonella Chiechi -- Outlier detection for mass spectrometric data / HyungJun Cho and Soo-Heang Eo -- Visualization and differential analysis of protein expression data using R / Tomé S. Silva and Nadège Richard -- False discovery rate estimation in proteomics / Suruchi Aggarwal and Amit Kumar Yadav -- Nonparametric bayesian model for nested clustering / Juhee Lee [and others] -- Set-based test procedures for the functional analysis of protein lists from differential analysis / Jochen Kruppa and Klaus Jung -- Classification of samples with order-restricted discriminant rules / David Conde [and others] -- Application of discriminant analysis and cross-validation on proteomics data / Julia Kuligowski, David Pérez-Guaita, and Guillermo Quintás -- Protein sequence analysis by proximities / Frank-Michael Schleif -- Statistical method for integrative platform analysis : application to integration of proteomic and microarray data / Xin Gao -- Data fusion in metabolomics and proteomics for biomarker discovery / Lionel Blanchet and Agnieszka Smolinska -- Reconstruction of protein networks using reverse-phase protein array data / Silvia von der Heyde [and others] -- Detection of unknown amino acid Substitutions using error-tolerant database search / Sven H. Giese, Franziska Zickmann, and Bernhard Y. Renard -- Data analysis strategies for protein modification identification / Yan Fu -- Dissecting the iTRAQ data analysis / Suruchi Aggarwal and Amit Kumar Yadav -- Statistical aspects in proteomic biomarker discovery / Klaus Jung |
| Summary |
This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although there is a large overlap between statistical methods for the different 'omics' fields, methods for analyzing data from proteomics experiments need their own specific adaptations. To satisfy that need, Statistical Analysis in Proteomics focuses on the planning of proteomics experiments, the preprocessing and analysis of the data, the integration of proteomics data with other high-throughput data, as well as some special topics. Written for the highly successful Methods in Molecular Biology series, the chapters contain the kind of detail and expert implementation advice that makes for a smooth transition to the laboratory. Practical and authoritative, Statistical Analysis in Proteomics serves as an ideal reference for statisticians involved in the planning and analysis of proteomics experiments, beginners as well as advanced researchers, and also for biologists, biochemists, and medical researchers who want to learn more about the statistical opportunities in the analysis of proteomics data |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Proteomics -- Statistical methods
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Proteomics -- statistics & numerical data
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Proteins.
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Science -- Life Sciences -- Biochemistry.
|
| Genre/Form |
Laboratory manuals.
|
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Manuels de laboratoire.
|
| Form |
Electronic book
|
| Author |
Jung, Klaus, 1977- editor
|
| LC no. |
2015952312 |
| ISBN |
9781493931064 |
|
1493931067 |
|
1493931059 |
|
9781493931057 |
|
