Blog
Mascot vs FragPipe: Uncovering endogenous proteolytic processing
Studying endogenous proteolytic processing, or N-terminomics, typically involves selective enrichment of protein N-termini. An alternative is to use the standard shotgun LC-MS/MS approach with the unenriched sample, which requires the database search to identify semi-specific peptides. Mascot Server 3.0 includes MS2PIP machine learning models for fragment intensity prediction, which can give a big boost to semi-specific identifications. Recent versions of [...]
Best MS2PIP model for Thermo Orbitrap
Mascot Server 3.0 greatly improves protein and peptide identification rates with Thermo Orbitrap instruments. The new version ships with MS2PIP, which provides fragment intensity predictions. When the database search results are correlated with predicted spectra, it boosts the number of statistically significant matches even with straightforward tryptic digests. CID and HCD models For qualitative work and label-free quantitation, Mascot Server [...]
Tutorial: Selecting the best MS2PIP model
Mascot Server 3.0 can refine database search results using predicted fragment intensities. The predictions are provided by MS2PIP, and Mascot ships with suitable models for common instrument types. This tutorial shows how to select the best model for your instrument and experiment. What is MS2PIP? MS2PIP is a tool for predicting the MS/MS fragmentation spectrum from a peptide sequence, charge [...]
Tutorial: Selecting the best DeepLC model
Mascot Server 3.0 can refine database search results using predicted retention times. The predictions are provided by DeepLC, and Mascot ships with twenty models for different gradient lengths, column types and peptide properties. This tutorial shows how to select the best model for your experiment. What is DeepLC? DeepLC is a retention time predictor that uses a convolutional neural network [...]
Predicted RT and fragment intensity in Mascot Server 3.0
A release candidate of the next version of Mascot Server is running on this website. One of the headline features in the preliminary release notes is refining results with machine learning, which includes integration with MS2Rescore. Below is a preview for you to enjoy while we are beta testing the new release. What is MS2Rescore? Mascot Server has shipped with [...]
How does rescoring with machine learning work?
Mascot Server ships with Percolator, which is an algorithm that uses semi-supervised machine learning to improve the discrimination between correct and incorrect spectrum identifications. This is often termed rescoring with machine learning. What exactly does it mean, and how does it work? Identifying correct matches using a score threshold When you submit a search against the target protein sequence database, [...]
Matrix Science at ASMS 2024
The ASMS 2024 conference was held in Anaheim, California, on 2-6 June 2024. It was great to see many of you at our booth as well as the annual Breakfast Meeting! We presented three talks at the meeting. If you were unable to attend, or want to review any of the material that was presented, the talks are summarised below [...]
30 years of Sequence Tags
This year we are celebrating 30 years of sequence tags. The technique was developed by Matthias Mann and Matthias Wilm while in the Protein and Peptide group at the European Molecular Biology Laboratory (EMBL). EMBL is itself celebrating its 50th Anniversary and has been an important center for science over that period. The sequence tag paper was published in 1994, [...]
Mascot workflow for LC-MS/MS data
Data analysis in mass spectrometry proteomics is complex and, nowadays, almost entirely software driven. Processing a raw file, peptide identification by database searching, protein inference and protein quantitation all have many steps and built-in assumptions, not to mention a huge number of parameters. Software continues to evolve as does best practice. Whether you are new to mass spectrometry proteomics or [...]
Tutorial: Creating custom reports in Mascot Distiller
Mascot Distiller 2.8 reports are written in Python, a commonly used programming language, and use Mascot Parser to access the search and quantitation results. We supply a range of standard reports, including reports for quality, clustering and statistical analysis, which we took a look at in an earlier blog article. In addition to these, you can develop your own reports [...]
How to run the public Mascot service
The public Mascot service running on this website recently had its 25th birthday: the service was launched in November 1998. The purpose is to let you evaluate the product before buying, but it’s also useful for small data sets and proteomics training courses. We’re a small company and our main activity is software development. The secrets to running the public [...]
Mascot security – guest users and administrators
Mascot Security is a role-based access system that allows administrators to control different aspects of privacy and priority access. It integrates with authentication systems like Microsoft Active Directory (AD) and various single sign-on systems. It can also be configured for a core lab, where search results can be shared with collaborators without them having access to the results of other groups. [...]
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