Florida State University Makes Advances in Pathogen Analysis


Scientists at Florida State University have designed an analysis tool that could be a game changer in pathogen analysis. The computational tool should allow scientists and researchers to study population genetics better. This could impact the study of disease distribution globally.

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Designing the Model

The tool that has been produced is a sophisticated mathematical model. It allows the simulation of genetic differences and their origins. It also allows more variations to be factored into the simulation including environmental differences. The details of the study can be found in Proceedings of the National Academy of Sciences.

Population statistics and an understanding of genetics are important in the large-scale fight against disease. The new model, known as the f-coalescent, is expected to help in the understanding of disease-causing organisms, or pathogens. The team developed it to expand on a previous model known as the n-coalescent. This was originally proposed in 1982 by John Kingman, a British scientist. One of the key limitations of that model is that it did not fully take into account the diversity in the population. The new f-coalescent model factors in the diverse experiences, environments, and locations that members of the population pass through at different times during their lifespans.
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Postdoctoral mathematician, Somayeh Mashayekhi, and computational biologist, Peter Beerli, who collaborated on the study looked at three data sets to develop their model. These were for cell and genetic data from humpback whales, malaria parasites, and the H1N1 influenza virus strain.

Promising Findings

The researchers found that the data for the pathogens, malaria and flu virus, indicated that there was a significant impact on these organisms from their environmental and other factors. For the whale data, however, these differences in the members of the population were not as significant. Studying organisms such as pathogens that evolve quickly is going to be enhanced by using the new model from the Florida State University researchers.

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