Author

W. Petrie

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Ecology· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:ecology & biodiversity· 1 Research Focus:host-pathogen & immune response· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

C. Vasquez· 2 shared A. B. B. Wilke· 1 shared A. Horton· 1 shared A. Janusauskaite· 1 shared A. Mantero· 1 shared A. Solis· 1 shared B. A. Borgert· 1 shared B. Kellner· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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2 shared papersEcology

C. Vasquez

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2 papers

Recent·Most cited

Using machine learning to understand microgeographic determinants of the Zika vector, Aedes aegypti

J. Alexander, A. B. B. Wilke, A. Mantero, C. Vasquez, W. Petrie, N. Kumar, J. C. Beier

This study uses machine learning to analyze mosquito population dynamics in Miami-Dade County, finding neighborhood-specific factors influencing Zika vector distribution.

bioRxiv · Mar 3, 2022Ecology

Modelling the distribution of Aedes aegypti and Aedes albopictus using climate, host density and interspecies competitive effects

B. Yang, B. A. Borgert, B. W. Alto, C. K. Boohene, P. Brabant, J. Brew, K. Deutsch, J. T. DeValerio, R. R. Dinglasan, D. Dixon, J. M. Faella, S. L. Fisher-Grainger, G. E. Glass, R. Hayes, D. F. Hoel, , D. A. T. Cummings

The paper develops a predictive model for the spatial distribution of Aedes aegypti and Aedes albopicti in Florida using climate, host density, and competitive interactions, achieving high validation accuracy.

bioRxiv · Dec 17, 2018 · PreprintEcology