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Indexed by:会议论文

Date of Publication:2018-01-01

Included Journals:CPCI-S

Volume:10954

Page Number:559-564

Key Words:Protein identification; Protein-spectrum matches; Machine learning; Rerank method

Abstract:Searching top-down spectra against a protein database has been a mainstream method for intact protein identification. Ranking true Protein-Spectrum Matches (PrSMs) over their false counterparts is a feasible method for improving protein identification results. In this paper, we propose a novel model called RPML (Rerank PrSMs based on Machine Learning) to rerank PrSMs in top-down proteomics. The experimental results on real data sets show that RPML can distinguish more correct PrSMs from incorrect ones. The source codes of algorithm are available at https://github.com/dqiong/spectra_ protein_match_ rerank.