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Kira Vyatkina

dblp:33/1031 · DBLP profile ↗
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6ranked-venue papers
1as first author
0since 2021 · last 2016
0000-0001-7356-1616ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 6 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › proteomics › peptide sequencing
de novo peptide sequencing
0.212016
Top-down analysis of protein samples by de novo sequencing techniques · Bioinform. 2016
Bioinformatics and computational biology › proteomics › post-translational modification
post-translational modification analysis
0.212016
Top-down analysis of protein samples by de novo sequencing techniques · Bioinform. 2016
Bioinformatics and computational biology
proteomics
0.212016
Top-down analysis of protein samples by de novo sequencing techniques · Bioinform. 2016
Bioinformatics and computational biology › proteomics › mass spectrometry proteomics
top-down proteomics
0.212016
Top-down analysis of protein samples by de novo sequencing techniques · Bioinform. 2016

Methods — techniques the papers use, named apart from their topics

string aggregation · 0.2de novo sequencing · 0.2
YearPublicationVenuePosition
2016 Top-down analysis of protein samples by de novo sequencing techniques
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: [email protected] or [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Kira Vyatkina, Lennard J. Dekker, Martijn M. VanDuijn, Nikola Tolic, Theo M. Luider, Ljiljana Pasa-Tolic, Pavel A. Pevzner
Bioinform.1
2013 On 2-Site Voronoi Diagrams Under Geometric Distance Functions
Gill Barequet, Matthew Dickerson, David Eppstein, David Hodorkovsky, Kira Vyatkina
J. Comput. Sci. Technol.5
2012 On Counting and Analyzing Empty Pseudo-triangles in a Point Set
Sergey Kopeliovich, Kira Vyatkina
ICCSA (1)2
2012 MORPH-PRO: A Novel Algorithm and Web Server for Protein Morphing
Natalie Castellana, Andrey Lushnikov, Piotr Rotkiewicz, Natasha Sefcovic, Pavel A. Pevzner, Adam Godzik, Kira Vyatkina
WABI7
2011 Tree Transformation through Vertex Contraction with Application to Skeletons
Arseny Smirnov, Kira Vyatkina
ICCSA (3)2
2007 Linear Axis for General Polygons: Properties and Computation
Vadim Trofimov, Kira Vyatkina
ICCSA (1)2