Training material for proteomics workflows in Galaxy
Before diving into this topic, we recommend you to have a look at:
You can also a public Galaxy instance which has been tested for the availability of the used tools. They are listed along with the tutorials above.
You can also use for these tutorials the dedicated Docker image:
docker run -d -p 8080:80 quay.io/galaxy/proteomics-training
It will launch a flavored Galaxy instance available on http://localhost:8080.
This material is maintained by:
- Florian Christoph Sigloch (firstname.lastname@example.org)
- Björn Grüning (email@example.com)
- Clemens Blank (firstname.lastname@example.org)
For any question related to this topic and the content, you can contact them.
This material was contributed to by:
- Florian Christoph Sigloch
- Björn Grüning
- Timothy J. Griffin
- Pratik Jagtap
- James Johnson
- Clemens Blank
- Kumar D, Yadav AK and Dash D: Choosing an Optimal Database for Protein Identification from Tandem Mass Spectrometry Data.
Vaudel M, et al.: Shedding light on black boxes in protein identification.
An extensive tutorial for peptide and protein identification, available at http://compomics.com/bioinformatics-for-proteomics. The material is completely based on freely available and open-source tools.
Cappadona S, et al.: Current challenges in software solutions for mass spectrometry-based quantitative proteomics
A comprehensive review of current quantitative techniques, their advantages and pitfalls.
Tholen S, et al.: Limited and Degradative Proteolysis in the Context of Posttranslational Regulatory Networks: Current Technical and Conceptional Advances
Review on LC-MS/MS based proteomic methods to identify neo-N-termini, e.g. generated by protease cleavage.