NovoGMET: De novo peptide sequencing using graphs with multiple edge types (GMET) for ETD/ECD Spectra

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Abstract

De novo peptide sequencing using tandem mass spectrometry (MS/MS) data has become a major computational method for sequence identification in recent years. With the development of new instruments and technology, novel computational methods have emerged with enhanced performance. However, there are only a few methods focusing on ECD/ETD spectra, which mainly contain variants of c-ions and z-ions. A de novo sequencing method for ECD/ETD spectra, NovoGMET, is presented here and compared with another successful de novo sequencing method, pNovo+, which has an option for ECD/ETD spectra. The proposed method applies a new spectrum graph with multiple edge types (GMET), considers multiple peptide tags, and integrates amino acid combination (AAC) and fragment ion charge information. Experiments conducted on three different datasets show that the average full length peptide identification accuracy of NovoGMET is as high as 88.70%, and that NovoGMET's average accuracy is more than 20% greater on all datasets as compared to pNovo+. © 2014 Springer International Publishing Switzerland.

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APA

Yan, Y., Kusalik, A. J., & Wu, F. X. (2014). NovoGMET: De novo peptide sequencing using graphs with multiple edge types (GMET) for ETD/ECD Spectra. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8492 LNBI, pp. 200–211). Springer Verlag. https://doi.org/10.1007/978-3-319-08171-7_18

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