Random Forest

2 methods · 2013–2018

Random Forest: Tree ensembles, used to predict fragment-ion intensities and to combine several sequencers’ output under a controlled error rate, rather than to sequence a spectrum directly.

Tree ensembles, used to predict fragment-ion intensities and to combine several sequencers’ output under a controlled error rate, rather than to sequence a spectrum directly.

The earliest of its 2 methods is MS2PIP (2013).

Methods 2
Papers describing them 2
Authors 5
Active 2013-09-27 to 2018-10-02
Kinds adjacent, post-processor
Acquisition DDA (2)

Methods (2)

Oldest first, by the paper that describes each one.

  • MS2PIP (2013): Original MS2PIP: random-forest predictor of MS/MS fragment-ion peak intensities used to rescore search-engine and de novo sequencing results. Later updates (2019 web server, 2024 DL backbone) live in algorithm.short_description.
  • PostNovo (2018): FDR-controlled ensembling

Papers describing them (2)

Authors (5)

Adriana I. Rizzo, Jacob R. Waldbauer, Lennart Martens, Samuel E. Miller, Sven Degroeve

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