Proteomics — Editorial Board Home

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Editorial Board

orcid logoPratik Jagtap avatar Pratik Jagtaporcid logoBjörn Grüning avatar Björn Grüningorcid logoSubina Mehta avatar Subina Mehtaorcid logoMelanie Föll avatar Melanie Föll

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Topic Materials

Material Contributions v2 Pre-requisites Follow up trainings Data on Zenodo Notebook Server Compatibility
Introduction to proteomics, protein identification, quantification and statistical modelling ❌ ✅
DIA Analysis using OpenSwathWorkflow ❌ ✅ ✅
EncyclopeDIA ❌ ✅
Label-free data analysis using MaxQuant ❌ ✅
Label-free versus Labelled - How to Choose Your Quantitation Method ✅ ❌
Library Generation for DIA Analysis ❌ ✅
MaxQuant and MSstats for the analysis of TMT data ❌ ✅
MaxQuant and MSstats for the analysis of label-free data ❌ ✅ ❌
Peptide and Protein ID using OpenMS tools ✅ ✅ ✅ ✅
Peptide and Protein ID using SearchGUI and PeptideShaker ✅ ✅
Peptide and Protein Quantification via Stable Isotope Labelling (SIL) ✅ ✅ ✅
Protein FASTA Database Handling ✅ ❌
Annotating a protein list identified by LC-MS/MS experiments ❌ ✅
Biomarker candidate identification ❌ ❌
Secretome Prediction ✅ ✅
Single Cell Proteomics data analysis with bioconductor-scp ✅ ✅
Statistical analysis of DIA data ❌ ✅ ✅
Detection and quantitation of N-termini (degradomics) via N-TAILS ✅ ❌
Mass spectrometry imaging: Loading and exploring MSI data ✅ ✅
Metaproteomics tutorial ❌ ✅
Multiomics data analysis using MultiGSEA ✅ ✅
Proteogenomics 1: Database Creation ❌ ✅ ✅
Proteogenomics 2: Database Search ✅ ✅ ✅ ✅
Proteogenomics 3: Novel peptide analysis ❌ ✅ ✅
metaQuantome 1: Data creation ❌ ✅ ✅
metaQuantome 2: Function ❌ ✅ ✅ ✅
metaQuantome 3: Taxonomy ❌ ✅ ✅ ✅
Machine Learning Modeling of Anticancer Peptides ❌ ✅
Peptide Library Data Analysis ❌ ✅
Clinical Metaproteomics 1: Database-Generation ✅ ✅ ✅ ✅
Clinical Metaproteomics 2: Discovery ✅ ✅ ✅ ✅
Clinical Metaproteomics 3: Verification ✅ ✅ ✅ ✅
Clinical Metaproteomics 4: Quantitation ✅ ✅ ✅ ✅
Clinical Metaproteomics 5: Data Interpretation ✅ ✅ ✅ ✅
Neoantigen 1a: Fusion-Database-Generation ✅ ✅ ✅ ✅
Neoantigen 1b: Non-Reference-Database-Generation ✅ ✅ ✅ ✅
Neoantigen 2: Database merge and FragPipe discovery ✅ ✅ ✅ ✅
Neoantigen 3: PepQuery2 Verification ✅ ✅ ✅ ✅
Neoantigen 4: Variant Annotation ✅ ✅ ✅ ✅
Neoantigen 5a: Predicting HLA Binding ✅ ✅ ✅ ✅
Neoantigen 5b: IEDB binding Validated Neopeptides ✅ ✅ ✅

Topic Workflows

Material Workflow Updated Version Tests Reports Comments
DIA Analysis using OpenSwathWorkflow DIA_Analysis_OSW Dec 14, 2025 1 ❌ ❌ ❌
EncyclopeDIA EncyclopeDIA-GTN Dec 14, 2025 2 ✅ ✅ ❌
Label-free data analysis using MaxQuant Proteomics: MaxQuant workflow Dec 14, 2025 6 ✅ ❌ ❌
Library Generation for DIA Analysis DIA_lib_OSW Dec 14, 2025 1 ❌ ❌ ❌
MaxQuant and MSstats for the analysis of TMT data MaxQuant MSstatsTMT Training Dec 14, 2025 1 ❌ ❌ ❌
MaxQuant and MSstats for the analysis of label-free data Proteomics: MaxQuant and MSstats for the analysis of label-free data Dec 14, 2025 4 ❌ ✅ ❌
Peptide and Protein ID using OpenMS tools Proteomics: Peptide and Protein ID using OpenMS Dec 14, 2025 6 ❌ ❌ ❌
Peptide and Protein ID using OpenMS tools Peptide And Protein ID Via OMS Using Two Search Engines Dec 14, 2025 4 ❌ ❌ ❌
Peptide and Protein ID using SearchGUI and PeptideShaker Peptide And Protein ID Tutorial Dec 14, 2025 4 ❌ ❌ ❌
Peptide and Protein ID using SearchGUI and PeptideShaker ProteinID SG PS Tutorial WF datasetCollection Dec 14, 2025 4 ❌ ❌ ❌
Peptide and Protein Quantification via Stable Isotope Labelling (SIL) Proteomics: Peptide and Protein Quantification via stable istobe labeling Dec 14, 2025 7 ✅ ❌ ❌
Protein FASTA Database Handling Proteomics: database handling Dec 14, 2025 5 ❌ ❌ ❌
Protein FASTA Database Handling Proteomics: database handling including mycoplasma Dec 14, 2025 6 ❌ ❌ ❌
Annotating a protein list identified by LC-MS/MS experiments 'Proteome Annotation' Dec 14, 2025 3 ❌ ❌ ❌
Annotating a protein list identified by LC-MS/MS experiments ProteoRE ProteomeAnnotation Tutorial (release 2.0) Dec 14, 2025 4 ❌ ❌ ❌
Biomarker candidate identification 'Biomarkers4Paris' Workflow Dec 14, 2025 3 ❌ ❌ ❌
Secretome Prediction Secreted Proteins Via GO Annotation And WoLF PSORT For shCTSB Paper Dec 14, 2025 3 ❌ ❌ ❌
Statistical analysis of DIA data DIA_analysis_MSstats Dec 14, 2025 2 ✅ ❌ ❌
Statistical analysis of DIA data DIA_analysis_MSstats Dec 14, 2025 2 ✅ ❌ ❌
Detection and quantitation of N-termini (degradomics) via N-TAILS Tails Triple Dimethyl OpenMS2.1 Dec 14, 2025 4 ❌ ❌ ❌
Mass spectrometry imaging: Loading and exploring MSI data MS Imaging Loading Exploring Data Dec 14, 2025 4 ❌ ❌ ❌
Metaproteomics tutorial Metaproteomics_GTN Dec 14, 2025 7 ❌ ❌ ❌
Multiomics data analysis using MultiGSEA MultiGSEA Dec 14, 2025 1 ✅ ✅ ❌
Proteogenomics 1: Database Creation Proteogenomics 1: Database Creation Dec 14, 2025 10 ❌ ✅ ❌
Proteogenomics 2: Database Search Proteogenomics 2: Database Search Dec 14, 2025 8 ❌ ✅ ❌
Proteogenomics 3: Novel peptide analysis GTN Proteogemics3 Novel Peptide Analysis Dec 14, 2025 7 ❌ ✅ ❌
metaQuantome 1: Data creation metaQuantome_datacreation_workflow Dec 14, 2025 3 ✅ ❌ ❌
metaQuantome 2: Function metaquantome-function-worklow Dec 14, 2025 2 ❌ ❌ ❌
metaQuantome 3: Taxonomy metaquantome-taxonomy-workflow Dec 14, 2025 2 ❌ ❌ ❌
Machine Learning Modeling of Anticancer Peptides PeptideML Dec 14, 2025 1 ❌ ❌ ❌
Peptide Library Data Analysis Copy of PeptideDataAnalysis (imported from uploaded file) Dec 14, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 1: Database-Generation WF1_Database_Generation_Workflow Dec 14, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 2: Discovery WF2_Discovery-Workflow Dec 14, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 3: Verification WF3_VERIFICATION_WORKFLOW Dec 14, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 4: Quantitation WF4_Quantitation_Workflow Dec 14, 2025 1 ❌ ❌ ❌
Clinical Metaproteomics 5: Data Interpretation WF5_Data_Interpretation_Worklow Dec 14, 2025 1 ❌ ❌ ❌

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Learning Pathways using materials from this Topic

image of a 3D protein folding structure
Clinical metaproteomics workflows within Galaxy

This learning path aims to teach you the basics of how to perform metaproteomics analysis of the clinical data within the Galaxy platform. You will learn how to use Galaxy for analysis and will be guided through the most common first steps of any metaproteomics database generation to searching the database, verifying the proteins/peptides, and data analysis.

beginner proteomics
image of neoantigen mutation
Neoantigen discovery using the iPepGen pipeline

This learning path introduces a comprehensive immunopeptidogenomics (iPepGen) workflow for neoantigen discovery using label-free mass spectrometry data. The modules guide you through fusion and variant database generation, peptide identification with FragPipe, peptide validation using PepQuery2, and immunogenicity assessment through HLA binding predictions and IEDB screening.

intermediate immunopeptidomics cancer proteogenomics label-free
image of a 3D protein folding structure
Proteogenomics

This learning path aims to teach you the basics of how to perform proteogenomics analysis of the Mass spectrometry data within the Galaxy platform. You will learn how to use Galaxy for analysis and will be guided through the most common first steps of any proteogenomics database generation to searching the database, followed by novel peptide data analysis.

beginner proteomics
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Events using materials from this Topic

TODO once this is merged: https://github.com/galaxyproject/training-material/pull/4963

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