Modeling Database Offers a Useful Tool for Determining Possible Parasites in Fish

The Journal of Parasitology presents a study featuring a new method of identifying parasites in various fish species. The results allow researches to identify known parasites in a similar fish species to estimate parasite compatibility with the host they are studying.

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The Journal of Parasitology Volume 99 Issue 1

Lawrence, KS (PRWEB) February 18, 2013

The Journal of Parasitology – We can learn a lot about fish from their parasites. One population of fish, for instance, might be distinguished from another of the same species by the parasites they carry. The study of parasites in fish now has a valuable tool. The Parasite Co-occurrence Modeler is an online system of parasitology data.

An article in The Journal of Parasitology reports about the features and performance of the Parasite Co-occurrence Modeler. It enables researchers to discover what parasites might be present in a particular host, a fish species in this case. Users can identify known parasites in a similar fish species to estimate parasite compatibility with the host they are researching.

By offering filter categories of habitat, geography, and phylogenesis, the Parasite Co-occurrence Modeler allows researchers to define these similarities among hosts. Maximum length, growth rate, life span, age at maturity, and trophic level can also be selected as parameters. Not only can researchers predict the occurrence of parasites in certain hosts, but they can also study parasite communities and their structure.

This system is a component of Fish Parasite Ecology Software Tools (FishPEST), which is designed to integrate with FishBase, a global species database of fish. The Parasite Co-occurrence Modeler is a free, online service available at http://purl.oclc.org/fishpest.

To test the Parasite Co-occurrence Modeler, authors of the current study created 12,400 parasite lists, applying all possible parameters of the model to 50 host fish. They then assessed the importance of each parameter by the frequency it appeared within the best models for each host. The phylogeny and geography filters yielded the best results, appearing in 88 percent of the best models, while habitat appeared in 64 percent. Trophic level was the top host dimension parameter, appearing in 41 percent of the best models.

While the modeler presents a flexible database that users can adjust to their needs, its main drawback is that helminth species are currently the only group of parasites available in the system for research.

Full text of “Predicting What Helminth Parasites a Fish Species Should Have Using Parasite Co-occurrence Modeler (PaCo),” The Journal of Parasitology, Vol. 99, No. 1, 2013, is available at http://www.journalofparasitology.org.


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