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Nizar Fawal

dblp:99/11328 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › comparative genomics
gene family analysis
0.112012
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
YearPublicationVenuePosition
2012 GECA: a fast tool for gene evolution and conservation analysis in eukaryotic protein families
abstract
Abstract 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