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Computational Proteomics

Our research in computational proteomics mainly lies in the area of top-down mass spectrometry, which is a novel highly promising technology for acquiring mass spectra. In contrast to the traditional bottom-up approach, it does not require protein digestion prior to tandem mass spectrometry step. Analysis of intact proteins offers certain advantages, such as possibilities to detect post-translational modifications in a coordinated fashion and to identify multiple protein species.  



Kira Vyatkina


Sonya Alexandrova

Mikhail Dvorkin

Yakov Sirotkin 

Interns (Summer 2011):

Maxim Gladkikh

Yuri Zemlyanskiy

Andrey Lushnikov

Ilya Makeev

Student (Fall 2011):

Ksenia Krasheninnikova


Current projects

Tag generation for top-down mass spectra

(joint project with Pavel Pevzner’s lab at UCSD)

A peptide sequence tag (PST) is a short sequence of amino acids. In bottom-up mass spectrometry, PSTs are successfully used for spectra interpretation; however, in the top-down case, possibilities of their generation and usage have not yet been explored sufficiently. In the frame of this project, we propose and analyze methods of PST generation for top-down spectra, and indicate their potential applications to spectra identification and mixed spectra interpretation.



Yakov Sirotkin, Xiaowen Liu, Maxim Gladkikh, Pavel Pevzner and Kira Vyatkina, “Peptide Sequence Tags for Top-Down Spectra”. (accepted to RECOMB CP 2012)



MS-Align+Tag (download)


Error correction for top-down mass spectra

(joint project with Pavel Pevzner’s lab at UCSD)

The procedure of spectrum interpretation starts with retrieval of isotopomer envelopes from a given spectrum, followed by derivation of monoisitopic masses from those envelopes. As a result, we obtain a deconvoluted spectrum. However, ±1Da errors are often observed in the masses composing deconvoluted spectra, which can impose serious problems in subsequent spectrum identification. The goal of this project is to eliminate this kind of errors.


Interpretation of mass spectra of substances resulting from chemical experiments

(joint project with Laboratory of Nanobiotechnologies, Academic University, headed by Corr. Mem. of RAS M.V. Dubina)

The goal of this project is to interpret mass spectra of substances, which are expected to contain peptides. Such hypothesis can be confirmed by retrieving an alphabet of amino acids composing the peptides present in a substance, and further explaining the given mass spectra.


Interpretation of multiplex mass spectra

Some mass spectra turn out to be produced from a mixture of proteins rather than from a single protein. They are usually referred to as mixed, or multiplex. This project aims to find a method for interpreting such spectra.


Completed projects

Protein identification using top-down spectra

(joint project with Pavel Pevzner’s lab at UCSD)

This project was devoted to development of a fast method for top-down protein identification, which allows searching for unexpected post-translational modifications. The proposed algorithm, MS-Align+, performs significantly better than previously existing approaches on two top-down datasets used for benchmarking  such software tools.



Xiaowen Liu, Yakov Sirotkin, Yufeng Shen, Gordon Anderson, Yihsuan S. Tsai, Ying S. Ting, David R. Goodlett, Richard D. Smith, Vineet Bafna and Pavel A. Pevzner,  “Protein identification using top-down spectra”. “Molecular and Cellular Proteomics”. 2011 Oct 25. [Epub ahead of print]


Protein morphing

(joint project with Pavel Pevzner’s lab at UCSD, Burnham Institute for Medical Research, and Joint Center for Structural Genomics, Bioinformatics Core)

Within this project, we developed an efficient algorithm for protein morphing based on linear interpolation and implemented it as a web server. 



Natalie E. Castellana, Andrey Lushnikov, Piotr Rotkiewicz, Natasha Sefcovic, Pavel A. Pevzner, and Adam Godzik, Kira Vyatkina, “MORPH-PRO: A Novel Algorithm and Web Server for Protein Morphing”. In Proc. The 12th workshop on Algorithms in Bioinformatics (WABI 2012), September 10-12, Ljubljana, Slovenia, LNCS 7534, Springer, 2012, 12pp. (to appear) (Appendix)



Our research in computational mass spectrometry is carried out in the frame of close collaboration with Pacific Northwest National Laboratory (PNNL).