CharmeRT: Boosting Peptide Identifications by Chimeric Spectra Identification and Retention Time Prediction | Zendy

Viktoria Dorfer | Zendy; S. Maltsev | Zendy; Stephan Winkler | Zendy; Karl Mechtler | Zendy

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CharmeRT: Boosting Peptide Identifications by Chimeric Spectra Identification and Retention Time Prediction

Author(s) -

Viktoria Dorfer,

S. Maltsev,

Stephan Winkler,

Karl Mechtler

Publication year - 2018

Publication title -

journal of proteome research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.644

H-Index - 161

eISSN - 1535-3907

pISSN - 1535-3893

DOI - 10.1021/acs.jproteome.7b00836

Subject(s) - retention time , workflow , boosting (machine learning) , identification (biology) , computer science , data mining , artificial intelligence , computational biology , chemistry , biological system , chromatography , biology , database , botany

Coeluting peptides are still a major challenge for the identification and validation of MS/MS spectra, but carry great potential. To tackle these problems, we have developed the here presented CharmeRT workflow, combining a chimeric spectra identification strategy implemented as part of the MS Amanda algorithm with the validation system Elutator, which incorporates a highly accurate retention time prediction algorithm. For high-resolution data sets this workflow identifies 38-64% chimeric spectra, which results in up to 63% more unique peptides compared to a conventional single search strategy.

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