Demo Data from EDBT 2026 / reviewers in the wild / expert
Nizar Fawal
dblp:99/11328
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2012
—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 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › comparative genomics
gene family analysis |
0.1 | 1 | 2012 | GECA: a fast tool for gene evolution and conservation analysis in eukaryotic protein families · Bioinform. 2012 |
Methods — techniques the papers use, named apart from their topics
protein alignment · 0.1CIWOG · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2012 | GECA: a fast tool for gene evolution and conservation analysis in eukaryotic protein familiesabstractAbstract Summary: GECA is a fast, user-friendly and freely-available tool for representing gene exon/intron organization and highlighting changes in gene structure among members of a gene family. It relies on protein alignment, completed with the identification of common introns in the corresponding genes using CIWOG. GECA produces a main graphical representation showing the resulting aligned set of gene structures, where exons are to scale. The important and original feature of GECA is that it combines these gene structures with a symbolic display highlighting sequence similarity between subsequent genes. It is worth noting that this combination of gene structure with the indications of similarities between related genes allows rapid identification of possible events of gain or loss of introns, or points to erroneous structural annotations. The output image is generated in a portable network graphics format which can be used for scientific publications. Availability and implementation: Web-implemented version and source code are freely available at https://peroxibase.toulouse.inra.fr/geca_input_demo.php and a detailed example can be found at https://peroxibase.toulouse.inra.fr/geca_instructions.php Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online. Nizar Fawal, Bruno Savelli, Christophe Dunand, Catherine Mathé |
Bioinform. | 1 |