Demo Data from EDBT 2026 / reviewers in the wild / expert
Maja Zagorscak
dblp:249/1444
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-1669-6482ORCID · 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 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
sequence analysis |
0.4 | 1 | 2019 | IGLOSS: iterative gapless local similarity search · Bioinform. 2019 |
Bioinformatics and computational biology › sequence analysis › sequence motif analysis
motif scanning |
0.1 | 1 | 2019 | IGLOSS: iterative gapless local similarity search · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
string matching · 0.4parameter estimation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | IGLOSS: iterative gapless local similarity searchabstractSUMMARY: Searching for local sequence patterns is one of the basic tasks in bioinformatics. Sequence patterns might have structural, functional or some other relevance, and numerous methods have been developed to detect and analyze them. These methods often depend on the wealth of information already collected. The explosion in the number of newly available sequences calls for novel methods to explore local sequence similarity. We have developed a new method for iterative motif scanning that will look for ungapped sequence patterns similar to a submitted query. Using careful parameter estimation and an adaptation of a fast string-matching algorithm, the method performs significantly better in this context than the existing software. AVAILABILITY AND IMPLEMENTATION: The IGLOSS web server is available at http://compbioserv.math.hr/igloss/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Braslav Rabar, Maja Zagorscak, Strahil Ristov, Martin Rosenzweig, Pavle Goldstein |
Bioinform. | 2 |