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E. H. Guseva

dblp:88/6441 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1997
—ORCID · none

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 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein analysis › protein bioinformatics
protein function analysis
0.011997
A bank of protein family patterns for rapid identification of possible functions of amino acid sequences · Comput. Appl. Biosci. 1997

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

profile · 0.0pattern construction from physicochemical properties · 0.0PROSITE · 0.0BLOCKS · 0.0
YearPublicationVenuePosition
1997 A bank of protein family patterns for rapid identification of possible functions of amino acid sequences
abstract
A method and software tool to develop patterns of protein families has been designed. These patterns are intended for the identification of local similarities in arbitrary amino acid sequences with proteins of the SWISS-PROT bank. The method is based on the physical, chemical and structural properties of amino acids. It assembles a 'best set' of elements (a pattern) for a given group of aligned related proteins. These elements provide discrimination between proteins of a family and representatives of other families or random sequences. The method combines the advantages of BLOCKS (automatic generation of multiple elements for protein groups), PROSITE (simplicity of element presentation) and matrices/profiles (different distinctions between amino acids for different positions of aligned sequences). Using our method, a data bank of protein family patterns, PROF_PAT, is produced. This data bank is based on the 27,752 amino acid sequences of SWISS-PROT bank release 24. The characteristics of patterns of 743 related protein groups are described. The results of comparisons of PROF_PAT patterns with the proteins of the SWISS-PROT bank are discussed.
Alexander G. Bachinsky, Andrey A. Yarigin, E. H. Guseva, V. A. Kulichkov, Lily Ph. Nizolenko
Comput. Appl. Biosci.3