Proteomics — Editorial Board Home

This is a new, experimental "Editorial Board Home" for a given topic. It is intended to provide a single place for maintainers and editorial board members to find out key information about their topic and identify action items.

Editorial Board

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

Action Items

Item Status Why you should do this
Summary Done ✅ Provide a sufficiently detailed summary of the topic to let learners know what they're learning about in this topic.
Sufficient Editorial Board Members Done ✅ (4 members) Having multiple people sharing the burden of being responsible for a specific topic can reduce board member burn-out in the long term.
Enable Subtopics Done ✅ Subtopics help organize the content and make it easier to navigate.
Annotate Funders Pending ❌ By annotating the funders of your topic's materials, you make it easier to write your grant reports later
Learning Pathway CTA Pending ❌ By providing a Learning Pathway CTA, we can help guide learners to the best resources for learning about this topic.

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 ❌ ❌ ❌ ✅ ❌
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 ❌ ❌ ❌ ✅ ❌
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 Metaproteiomics 1: Database-Generation ✅ ✅ ✅ ✅ ❌
Clinical Metaproteomics 2: Discovery ✅ ✅ ✅ ✅ ❌
Clinical Metaproteomics 3: Verification ✅ ✅ ✅ ✅ ❌
Clinical Metaproteomics 4: Quantitation ✅ ✅ ✅ ✅ ❌
Clinical Metaproteomics 5: Data Interpretation ✅ ✅ ✅ ✅ ❌

Topic Workflows

Material Workflow Updated Version Tests Reports Comments
DIA Analysis using OpenSwathWorkflow DIA_Analysis_OSW Dec 22, 2024 1 ❌ ❌ ❌
EncyclopeDIA EncyclopeDIA-GTN Dec 22, 2024 2 ✅ ✅ ❌
Label-free data analysis using MaxQuant Proteomics: MaxQuant workflow Dec 22, 2024 6 ✅ ❌ ❌
Library Generation for DIA Analysis DIA_lib_OSW Dec 22, 2024 1 ❌ ❌ ❌
MaxQuant and MSstats for the analysis of TMT data MaxQuant MSstatsTMT Training Dec 22, 2024 1 ❌ ❌ ❌
MaxQuant and MSstats for the analysis of label-free data Proteomics: MaxQuant and MSstats LFQ workflow Dec 22, 2024 3 ❌ ❌ ❌
Peptide and Protein ID using OpenMS tools Proteomics: Peptide and Protein ID using OpenMS Dec 22, 2024 6 ❌ ❌ ❌
Peptide and Protein ID using OpenMS tools Peptide And Protein ID Via OMS Using Two Search Engines Dec 22, 2024 4 ❌ ❌ ❌
Peptide and Protein ID using SearchGUI and PeptideShaker Peptide And Protein ID Tutorial Dec 22, 2024 4 ❌ ❌ ❌
Peptide and Protein ID using SearchGUI and PeptideShaker ProteinID SG PS Tutorial WF datasetCollection Dec 22, 2024 4 ❌ ❌ ❌
Peptide and Protein Quantification via Stable Isotope Labelling (SIL) Proteomics: Peptide and Protein Quantification via stable istobe labeling Dec 22, 2024 7 ✅ ❌ ❌
Protein FASTA Database Handling Proteomics: database handling Dec 22, 2024 5 ❌ ❌ ❌
Protein FASTA Database Handling Proteomics: database handling including mycoplasma Dec 22, 2024 6 ❌ ❌ ❌
Annotating a protein list identified by LC-MS/MS experiments 'Proteome Annotation' Dec 22, 2024 3 ❌ ❌ ❌
Annotating a protein list identified by LC-MS/MS experiments ProteoRE ProteomeAnnotation Tutorial (release 2.0) Dec 22, 2024 4 ❌ ❌ ❌
Biomarker candidate identification 'Biomarkers4Paris' Workflow Dec 22, 2024 3 ❌ ❌ ❌
Secretome Prediction Secreted Proteins Via GO Annotation And WoLF PSORT For shCTSB Paper Dec 22, 2024 3 ❌ ❌ ❌
Statistical analysis of DIA data DIA_analysis_MSstats Dec 22, 2024 2 ✅ ❌ ❌
Statistical analysis of DIA data DIA_analysis_MSstats Dec 22, 2024 2 ✅ ❌ ❌
Detection and quantitation of N-termini (degradomics) via N-TAILS Tails Triple Dimethyl OpenMS2.1 Dec 22, 2024 4 ❌ ❌ ❌
Mass spectrometry imaging: Loading and exploring MSI data MS Imaging Loading Exploring Data Dec 22, 2024 4 ❌ ❌ ❌
Metaproteomics tutorial Metaproteomics_GTN Dec 22, 2024 7 ❌ ❌ ❌
Proteogenomics 1: Database Creation GTN Proteogenomics1 Database Creation Dec 22, 2024 8 ❌ ❌ ❌
Proteogenomics 2: Database Search GTN Proteogemics2 Database Search Dec 22, 2024 7 ❌ ❌ ❌
Proteogenomics 3: Novel peptide analysis GTN Proteogemics3 Novel Peptide Analysis Dec 22, 2024 6 ❌ ❌ ❌
metaQuantome 1: Data creation metaQuantome_datacreation_workflow Dec 22, 2024 3 ✅ ❌ ❌
metaQuantome 2: Function metaquantome-function-worklow Dec 22, 2024 2 ❌ ❌ ❌
metaQuantome 3: Taxonomy metaquantome-taxonomy-workflow Dec 22, 2024 2 ❌ ❌ ❌
Machine Learning Modeling of Anticancer Peptides PeptideML Dec 22, 2024 1 ❌ ❌ ❌
Peptide Library Data Analysis Copy of PeptideDataAnalysis (imported from uploaded file) Dec 22, 2024 1 ❌ ❌ ❌
Clinical Metaproteiomics 1: Database-Generation WF1_Database_Generation_Workflow Dec 22, 2024 1 ❌ ❌ ❌
Clinical Metaproteomics 2: Discovery WF2_Discovery-Workflow Dec 22, 2024 1 ❌ ❌ ❌
Clinical Metaproteomics 3: Verification WF3_VERIFICATION_WORKFLOW Dec 22, 2024 1 ❌ ❌ ❌
Clinical Metaproteomics 4: Quantitation WF4_Quantitation_Workflow Dec 22, 2024 1 ❌ ❌ ❌
Clinical Metaproteomics 5: Data Interpretation WF5_Data_Interpretation_Worklow Dec 22, 2024 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 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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