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Robert Vaser

dblp:185/8157 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · unresolved

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein sequence analysis
protein database search
0.212016
SWORD - a highly efficient protein database search · Bioinform. 2016
Bioinformatics and computational biology
sequence alignment
0.212016
SWORD - a highly efficient protein database search · Bioinform. 2016
Bioinformatics and computational biology
sequence analysis
0.212016
SWORD - a highly efficient protein database search · Bioinform. 2016

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

heuristic search · 0.2
YearPublicationVenuePosition
2016 SWORD - a highly efficient protein database search
abstract
MOTIVATION: Protein database search is one of the fundamental problems in bioinformatics. For decades, it has been explored and solved using different exact and heuristic approaches. However, exponential growth of data in recent years has brought significant challenges in improving already existing algorithms. BLAST has been the most successful tool for protein database search, but is also becoming a bottleneck in many applications. Due to that, many different approaches have been developed to complement or replace it. In this article, we present SWORD, an efficient protein database search implementation that runs 8-16 times faster than BLAST in the sensitive mode and up to 68 times faster in the fast and less accurate mode. It is designed to be used in nearly all database search environments, but is especially suitable for large databases. Its sensitivity exceeds that of BLAST for majority of input datasets and provides guaranteed optimal alignments. AVAILABILITY AND IMPLEMENTATION: Sword is freely available for download from https://github.com/rvaser/sword CONTACT: [email protected] and [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Robert Vaser, Dario Pavlovic, Mile Sikic
Bioinform.1