Proteomics Data Analysis, 1st ed. 2021 Methods in Molecular Biology Series, Vol. 2361

Part I: Data Analysis for Gel-Based Proteomics

1. Two-Dimensional Gel Electrophoresis Image Analysis

            Elisa Robotti, Elisa Calà, and Emilio Marengo

2. Chemometric Tools for 2D-PAGE Data Analysis

            Elisa Robotti, Elisa Calà, and Emilio Marengo

Part II: Data Analysis for Gel-Free Proteomics

3. Software Options for the Analysis of MS Proteomic Data

            Avinash Yadav, Federica Marini, Alessandro Cuomo, and Tiziana Bonaldi

4. Analysis of Label-Based Quantitative Proteomics Data Using IsoProt

            Johannes Griss and Veit Schwämmle

5. Quantification of Changes in Protein Expression Using SWATH Proteomics

            Clarissa Braccia, Nara Liessi, and Andrea Armirotti

6. Data Processing and Analysis for DIA-Based Phosphoproteomics Using Spectronaut

            Ana Martinez-Val, Dorte Breinholdt Bekker-Jensen, Alexander Hogrebe, and Jesper Velgaard Olsen

7. Enhanced Glycopeptide Identification Using a GlyConnect Compozitor-Derived Glycan Composition File

            Julien Mariethoz, Catherine Hayes, and Frédérique Lisacek

8. Elaboration Pipeline for the Management of MALDI-MS Imaging Datasets

            Andrew Smith, Isabella Piga, Vanna Denti, Clizia Chinello, and Fulvio Magni

            Marta Lualdi and Mauro Fasano

Part III: Proteomics Data Interpretation

10. ORA, FCS, and PT Strategies in Functional Enrichment Analysis

            Marco Fernandes and Holger Husi

11. A Strategy for the Annotation and GO Enrichment Analysis of a List of Differentially Expressed Proteins Using ProteoRE

            Florence Combes, Valentin Loux, and Yves Vandenbrouck

12. Protein Subcellular Localization Prediction

            Elettra Barberis, Emilio Marengo, and Marcello Manfredi

13. Protein Secretion Prediction Tools and Extracellular Vesicles Databases

            Daniela Cecconi, Claudia Di Carlo, and Jessica Brandi

14. Databases for Protein-Protein Interactions

            Natsu Nakajima, Tatsuya Akutsu, and Ryuichiro Nakato

15. Machine and Deep Learning for Prediction of Subcellular Localization

            Gaofeng Pan, Chao Sun, Zijun Liao, and Jijun Tang

16. Deep Learning for Protein-Protein Interaction Site Prediction

            Arian R. Jamasb, Ben Day, Cătălina Cangea, Pietro Liò, and Tom L. Blundell

Part IV: Proteomics Data Integration with Other -Omics

17. Integrative Analysis of Incongruous Cancer Genomics and Proteomics Datasets

            Karla Cervantes-Gracia, Richard Chahwan, and Holger Husi

18. Integration of Proteomics and Other Omics Data

Includes cutting-edge techniques

Provides step-by-step detail essential for reproducible results

Contains key implementation advice from the experts