MS2PIP

adjacent · Random Forest

MS2PIP: adjacent · Random Forest. Predictor of MS/MS fragment-ion peak intensities, used to rescore search-engine and de novo sequencing results. Introduced in 2013 as a random-forest model; the 2019…

Predictor of MS/MS fragment-ion peak intensities, used to rescore search-engine and de novo sequencing results. Introduced in 2013 as a random-forest model; the 2019 web-server update added models for further fragmentation methods, instruments and labelling techniques, and the 2023 update added tryptic, non-tryptic, immunopeptide and TMT models and proteome-wide predicted spectral libraries with DeepLC retention times.

Kind	adjacent
Deep learning	no
Acquisition	DDA
Family	Random Forest

Code

• https://github.com/compomics/ms2pip

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Papers describing it (3)

• MS2PIP: a tool for MS/MS peak intensity prediction (2013, Bioinformatics, peer-reviewed)
• Updated MS²PIP web server delivers fast and accurate MS² peak intensity prediction for multiple fragmentation methods, instruments and labeling techniques (2019, Nucleic Acids Research, peer-reviewed)
• Updated MS²PIP web server supports cutting-edge proteomics applications (2023, Nucleic Acids Research, peer-reviewed)

Authors (9)

Sven Degroeve, Lennart Martens, Ralf Gabriels, Arthur Declercq, Robbin Bouwmeester, Cristina Chiva, Eduard Sabidó, Aurélie Hirschler, Christine Carapito

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