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F. Dyrlund, L. R. Thomsen, T. a. Nielsen, L. Brøndum, T. Wang, I. B. Thøgersen and J. J. Enghild, Characterization of the gila monster (Heloderma suspectum suspectum) venom proteome, J. Proteomics, 2015, 117, 1–11. K. D. Zaqueo, A. M. Kayano, R. Simões-Silva, L. S. Moreira-Dill, C. F. C. Fernandes, A. L. Fuly, V. G. Maltarollo, K. M. Honório, S. L. da Silva, G. Acosta, M. A. O. Caballol, E. de Oliveira, F. Albericio, L. a Calderon, A. M. Soares and R. G. Stábeli, Isolation and biochemical characterization of a new thrombin-like serine protease from Bothrops pirajai snake venom, BioMed Res.

5(a) illustrates an example peptide. 5(b). If peaks are found at the corresponding locations in the spectrum, a positive reward should be added to the score. Otherwise, a negative penalty should be added. Let f(m) denote such a reward/penalty scheme. Notice that the definition of f(m) only requires M and the spectrum, but not the actual peptide sequence. 5 (a) An example peptide. Each prefix mass mi defines a fragmentation site. (b) In general, a fragmentation at prefix mass m produces a b-ion with mass m + 1 and a y-ion with mass M − m + 19.

Johnson, Sequence database searches via de novo peptide sequencing by tandem mass spectrometry, Rapid Commun. , 1997, 11, 1067–1075. B. Ma, K. Zhang, C. Hendrie, C. Liang, M. Li, A. Doherty-Kirby and G. Lajoie, PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry, Rapid Commun. , 2003, 17, 2337–2342. A. Frank and P. A. Pevzner, PepNovo: de novo peptide sequencing via probabilistic network modeling, Anal. , 2005, 77(4), 964–973. B. Ma, Novor: Real-Time Peptide de Novo Sequencing Software, J.

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