Demo Data from EDBT 2026 / reviewers in the wild / expert
Robert Vaser
dblp:185/8157
· DBLP profile ↗
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
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › protein sequence analysis
protein database search |
0.2 | 1 | 2016 | SWORD - a highly efficient protein database search · Bioinform. 2016 |
Bioinformatics and computational biology
sequence alignment |
0.2 | 1 | 2016 | SWORD - a highly efficient protein database search · Bioinform. 2016 |
Bioinformatics and computational biology
sequence analysis |
0.2 | 1 | 2016 | SWORD - a highly efficient protein database search · Bioinform. 2016 |
Methods — techniques the papers use, named apart from their topics
heuristic search · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | SWORD - a highly efficient protein database searchabstractMOTIVATION: 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 |