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Anna V. Sokolova

dblp:176/9821 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0002-2772-7395ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1

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 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › structural biology
small angle x-ray scattering analysis
0.212016
DARA: a web server for rapid search of structural neighbours using solution small angle X-ray scattering data · Bioinform. 2016
Bioinformatics and computational biology › protein structure prediction › template-based modeling
fold recognition
0.112016
DARA: a web server for rapid search of structural neighbours using solution small angle X-ray scattering data · Bioinform. 2016
Bioinformatics and computational biology
structural bioinformatics
0.112016
DARA: a web server for rapid search of structural neighbours using solution small angle X-ray scattering data · Bioinform. 2016

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

SAXS profile matching · 0.2
YearPublicationVenuePosition
2016 DARA: a web server for rapid search of structural neighbours using solution small angle X-ray scattering data
abstract
MOTIVATION: Small angle X-ray scattering (SAXS) is an established method for studying biological macromolecules in solution, whereby the experimental scattering patterns relate to the quaternary and tertiary structure of the macromolecule. Here we present DARA, a web-server, that queries over 150 000 scattering profiles pre-computed from the high resolution models of macromolecules and biological assemblies in the Protein Data Bank, to rapidly find nearest neighbours of a given experimental or theoretical SAXS pattern. Identification of the best scattering equivalents provides a straightforward and automated way of structural assessment of macromolecules based on a SAXS profile. DARA results are useful e.g. for fold recognition and finding of biologically active oligomers. AVAILABILITY AND IMPLEMENTATION: http://dara.embl-hamburg.de/.
Alexey Kikhney, Alejandro Panjkovich, Anna V. Sokolova, Dmitri I. Svergun
Bioinform.3