Sensitive and Specific Spectral Library Searching with CompOmics Spectral Library Searching Tool and Percolator.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of proteome research"
DOI: 10.1021/acs.jproteome.2c00075
Abstract: Maintaining high sensitivity while limiting false positives is a key challenge in peptide identification from mass spectrometry data. Here, we investigate the effects of integrating the machine learning-based postprocessor Percolator into our spectral library searching… read more here.
Keywords: spectral library; percolator; compomics spectral; searching tool ... See more keywords
A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of proteome research"
DOI: 10.1021/acs.jproteome.7b00767
Abstract: Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets… read more here.
Keywords: large scale; svm; analysis; percolator ... See more keywords
A machine learning strategy that leverages large datasets to boost statistical power in small-scale experiments
Sign Up to like & getrecommendations! Published in 2020 at "Journal of proteome research"
DOI: 10.1021/acs.jproteome.9b00780
Abstract: Machine learning methods have proven invaluable for increasing the sensitivity of peptide detection in proteomics experiments. Most modern tools, such as Percolator and PeptideProphet, use semi-supervised algorithms to learn models directly from the datasets that… read more here.
Keywords: machine learning; power; scale experiments; small scale ... See more keywords