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Statistical Analysis in Proteomics

  • Kartonierter Einband
  • 313 Seiten
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This valuable collection aims to provide a collection of frequently used statistical methods in the field of proteomics. Although ... Weiterlesen
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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.

Includes cutting-edge methods for the study of the statistical analysis of proteomics

Provides step-by-step detail essential for reproducible results

Contains key notes and implementation advice from the experts


Part I: Proteomics, Study Design, and Data Processing

1. Introduction to Proteomics Technologies

Christof Lenz and Hassan Dihazi

2. Topics in Study Design and Analysis for Multi-Stage Clinical Proteomics Studies

Irene Sui Lan Zeng

3. Preprocessing and Analysis of LC-MS-Based Proteomic Data

Tsung-Heng Tsai, Minkun Wang, and Habtom W. Ressom

4. Normalization of Reverse Phase Protein Microarray Data: Choosing the Best Normalization Analyte

Antonella Chiechi

5. Outlier Detection for Mass Spectrometric Data

HyungJun Cho and Soo-Heang Eo

Part II: Group Comparisons

6. Visualization and Differential Analysis of Protein Expression Data Using R

Tomé S. Silva and Nadège Richard

7. False Discovery Rate Estimation in Proteomics

Suruchi Aggarwal and Amit Kumar Yadav

8. A Nonparametric Bayesian Model for Nested Clustering

Juhee Lee, Peter Müller, Yitan Zhu, and Yuan Ji

9. Set-Based Test Procedures for the Functional Analysis of Protein Lists from Differential Analysis

Jochen Kruppa and Klaus Jung

Part III: Classification Methods

10. Classification of Samples with Order Restricted Discriminant Rules

David Conde, Miguel A. Fernández, Bonifacio Salvador, and Cristina Rueda

11. Application of Discriminant Analysis and Cross Validation on Proteomics Data

Julia Kuligowski, David Pérez-Guaita, and Guillermo Quintás

12. Protein Sequence Analysis by Proximities

Frank-Michael Schleif

Part IV: Data Integration

13. Statistical Method for Integrative Platform Analysis: Application to Integration of Proteomic and Microarray Data

Xin Gao

14. Data Fusion in Metabolomics and Proteomics for Biomarkers Discovery

Lionel Blanchet and Agnieszka Smolinska

Part V: Special Topics

15. Reconstruction of Protein Networks Using Reverse Phase Protein Array Data

Silvia von der Heyde, Johanna Sonntag, Frank Kramer, Christian Bender, Ulrike Korf, and Tim Beißbarth

16. Detection of Unknown Amino Acid Substitutions Using Error-Tolerant Database Search

Sven H. Giese, Franziska Zickmann, and Bernhard Y. Renard

17. Data Analysis Strategies for Protein Modification Identification

Yan Fu

18. Dissecting the iTRAQ Data Analysis

Suruchi Aggarwal and Amit Kumar Yadav

19. Statistical Aspects in Proteomic Biomarker Discovery

Klaus Jung


Titel: Statistical Analysis in Proteomics
EAN: 9781493979875
ISBN: 978-1-4939-7987-5
Format: Kartonierter Einband
Herausgeber: Springer, Berlin
Genre: Biologie
Anzahl Seiten: 313
Gewicht: 756g
Größe: H14mm x B254mm x T177mm
Jahr: 2019
Auflage: Softcover reprint of the original 1st ed. 2016

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