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Bioinformatics. 2016 Sep 15;32(18):2753-9. doi: 10.1093/bioinformatics/btw307. Epub 2016 May 14.

Top-down analysis of protein samples by de novo sequencing techniques.

Author information

1
Algorithmic Biology Laboratory, Saint Petersburg Academic University, St Petersburg, Russia Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, St Petersburg, Russia.
2
Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA.
3
Department of Neurology, Erasmus University Medical Center, Rotterdam, The Netherlands.
4
Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA.
5
Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA, USA.
6
Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University, St Petersburg, Russia Department of Computer Science and Engineering, University of California, San Diego, CA, USA.

Abstract

MOTIVATION:

Recent technological advances have made high-resolution mass spectrometers affordable to many laboratories, thus boosting rapid development of top-down mass spectrometry, and implying a need in efficient methods for analyzing this kind of data.

RESULTS:

We describe a method for analysis of protein samples from top-down tandem mass spectrometry data, which capitalizes on de novo sequencing of fragments of the proteins present in the sample. Our algorithm takes as input a set of de novo amino acid strings derived from the given mass spectra using the recently proposed Twister approach, and combines them into aggregated strings endowed with offsets. The former typically constitute accurate sequence fragments of sufficiently well-represented proteins from the sample being analyzed, while the latter indicate their location in the protein sequence, and also bear information on post-translational modifications and fragmentation patterns.

AVAILABILITY AND IMPLEMENTATION:

Freely available on the web at http://bioinf.spbau.ru/en/twister

CONTACT:

vyatkina@spbau.ru or ppevzner@ucsd.edu

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
27187201
PMCID:
PMC6280873
DOI:
10.1093/bioinformatics/btw307
[Indexed for MEDLINE]
Free PMC Article

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