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Roman R. Kapaev

dblp:151/2642 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0002-2753-8666ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural biology
molecular structure determination
0.312018
GRASS: semi-automated NMR-based structure elucidation of saccharides · Bioinform. 2018
Bioinformatics and computational biology › structural biology
NMR structure determination
0.312018
GRASS: semi-automated NMR-based structure elucidation of saccharides · Bioinform. 2018

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

NMR simulation · 0.3
YearPublicationVenuePosition
2018 GRASS: semi-automated NMR-based structure elucidation of saccharides
abstract
Motivation: Carbohydrates play crucial roles in various biochemical processes and are useful for developing drugs and vaccines. However, in case of carbohydrates, the primary structure elucidation is usually a sophisticated task. Therefore, they remain the least structurally characterized class of biomolecules, and it hampers the progress in glycochemistry and glycobiology. Creating a usable instrument designed to assist researchers in natural carbohydrate structure determination would advance glycochemistry in biomedical and pharmaceutical applications. Results: We present GRASS (Generation, Ranking and Assignment of Saccharide Structures), a novel method for semi-automated elucidation of carbohydrate and derivative structures which uses unassigned 13C NMR spectra and information obtained from chromatography, optical, chemical and other methods. This approach is based on new methods of carbohydrate NMR simulation recently reported as the most accurate. It combines a broad diversity of supported structural features, high accuracy and performance. Availability and implementation: GRASS is implemented in a free web tool available at http://csdb.glycoscience.ru/grass.html. Contact: [email protected] or [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.
Roman R. Kapaev, Philip V. Toukach
Bioinform.1