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BioNet: Peptide Mass-Spectrum Prediction

https://doi.org/10.25205/1818-7900-2020-18-2-31-42

Abstract

The importance of the biological properties of proteins to cells cause actively exploring their amino acid composition (primary structure). The versatile tool of cell proteome exploring is mass-spectroscopy. The interpretation of mass-spectroscopy data is complex challenge because it remains uncertain peptide dissociation mechanisms and external factor influence to peptide fragmentation process. Moreover, a lot of mass-spectroscopy data is required to enhancement existing or development novel algorithms to interpret peptide mass-spectra. The article describes development of algorithm for in silico generation peptide mass-spectra covered the problem of influence noncanonical amino acid composition and posttranslational modifications to dissociation process. Developed algorithm was compared with analogues and evaluated over experimental data.

About the Authors

R. Yu. Epifanov
Novosibirsk State University
Russian Federation


D. A. Afonnikov
Novosibirsk State University; Institute of Cytology and Genetics SB RAS
Russian Federation


Review

For citations:


Epifanov R.Yu., Afonnikov D.A. BioNet: Peptide Mass-Spectrum Prediction. Vestnik NSU. Series: Information Technologies. 2020;18(2):31-42. (In Russ.) https://doi.org/10.25205/1818-7900-2020-18-2-31-42

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ISSN 1818-7900 (Print)
ISSN 2410-0420 (Online)