Related Experiment Video
Updated: Apr 26, 2026
10:37
Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
11.4K
A standardized framing for reporting protein identifications in mzIdentML 1.2
Sean L Seymour1, Terry Farrah, Pierre-Alain Binz
1AB SCIEX, Redwood City, CA, USA.
Proteomics
|August 6, 2014
Summary
Comparing protein identifications from different tools is challenging. We introduce a standardized framework to improve cross-tool comparisons in proteomics, aiding collaborative projects and data sharing.
Area of Science:
- Proteomics
- Bioinformatics
- Data Standards
Background:
- Protein identification in bottom-up proteomics is complex.
- Comparing results from different inference tools is a major challenge.
- This hinders collaborative efforts like the Human Proteome Project and PRIDE database.
Purpose of the Study:
- To present a framework for reporting protein identifications.
- To enhance the comparability of results from various inference tools.
- To standardize terminology within the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard.
Main Methods:
- Developed a standardized terminology for protein identification results.
- Associated the terminology with the mzIdentML standard.
- Proposed adoption of this terminology by software developers.
Main Results:
- The framework allows for differing methodologies while standardizing output.
- No changes to the core mzIdentML model are required.
- New guidelines will be released in mzIdentML specification version 1.2.
Conclusions:
- The proposed framework will improve the comparison of protein identification data.
- Standardization facilitates collaboration and data integration in proteomics.
- Adoption by software developers is crucial for implementation.
