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Updated: Jul 7, 2026
09:40
Phage Phenomics: Physiological Approaches to Characterize Novel Viral Proteins
Published on: June 11, 2015
Prophinder: a computational tool for prophage prediction in prokaryotic genomes
Gipsi Lima-Mendez1, Jacques Van Helden, Ariane Toussaint
1Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, 1050 Bruxelles, Belgium. gipsi@scmbb.ulb.ac.be
Bioinformatics (Oxford, England)
|February 2, 2008
Summary
Prophinder predicts prophages to expand the limited phage sequence space, aiding research into prophage roles in bacteriophage evolution and gene transfer. This tool supports understanding gene shuffling between prophages and infecting phages.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- The current phage sequence space is sparse, with an estimated 100 million species yet to be discovered.
- Understanding prophages is crucial for studying bacteriophage evolution and gene dynamics.
Purpose of the Study:
- To introduce Prophinder, a tool for predicting prophages.
- To facilitate the expansion of the known phage sequence space.
- To enable deeper investigations into the contribution of prophages to the bacteriophage gene pool.
Main Methods:
- Prophinder integrates a prediction database, web server, and web service.
- Systematic prediction of prophages using computational approaches.
Main Results:
- Prophinder provides a method for predicting prophages, addressing gaps in sequence data.
- Predicted prophages contribute to a more comprehensive understanding of phage diversity.
Conclusions:
- Prophinder aids in filling gaps in the phage sequence space.
- Reliable prophage predictions will advance studies on gene shuffling and bacteriophage evolution.
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