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Akunevich Anastasia Aleksandrovna Khrustalev Vladislav Victorovich Khrustaleva Tatyana Aleksandrovna Poboinev Victor Vitoldovich Shalygo Nikolai Vladimirovich Stojarov Aleksander Nicolaevich Arutyunyan Alexander Migranovich Kordyukova Larisa Valentinovna Sapon Yehor Gennadyevich 《The protein journal》2022,41(2):245-259
The Protein Journal - An interplay between monomeric and dimeric forms of human epidermal growth factor (EGF) affecting its interaction with EGF receptor (EGFR) is poorly understood. While EGF... 相似文献
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Michele Mishto Yehor Horokhovskyi John A. Cormican Xiaoping Yang Steven Lynham Henning Urlaub Juliane Liepe 《Proteomics》2022,22(10):2100226
Unconventional epitopes presented by HLA class I complexes are emerging targets for T cell targeted immunotherapies. Their identification by mass spectrometry (MS) required development of novel methods to cope with the large number of theoretical candidates. Methods to identify post-translationally spliced peptides led to a broad range of outcomes. We here investigated the impact of three common database search engines – that is, Mascot, Mascot+Percolator, and PEAKS DB – as final identification step, as well as the features of target database on the ability to correctly identify non-spliced and cis-spliced peptides. We used ground truth datasets measured by MS to benchmark methods’ performance and extended the analysis to HLA class I immunopeptidomes. PEAKS DB showed better precision and recall of cis-spliced peptides and larger number of identified peptides in HLA class I immunopeptidomes than the other search engine strategies. The better performance of PEAKS DB appears to result from better discrimination between target and decoy hits and hence a more robust FDR estimation, and seems independent to peptide and spectrum features here investigated. 相似文献
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