Author

N. Fountain-Jones

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· 1 Physiology· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 2 Organism:Arabidopsis· 1 Research Focus:benchmarking· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

A. A. Costa· 1 shared C. Packer· 1 shared G. Machado· 1 shared I. Munoz· 1 shared J. E. Rabinovich· 1 shared M. E. Craft· 1 shared M. Mendoza· 1 shared P. E. Schilman· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 16 mutual co-author links

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1 shared paperPhysiology

A. A. Costa

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2 papers

Recent·Most cited

Machine-learning model led design to experimentally test species thermal limits: the case of kissing bugs (Triatominae)

J. E. Rabinovich, A. A. Costa, I. Munoz, P. E. Schilman, N. Fountain-Jones

This paper uses machine learning to guide experimental design for testing thermal tolerance in kissing bugs, identifying temperature and exposure time as key factors.

bioRxiv · Oct 5, 2020Physiology

How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure

N. Fountain-Jones, G. Machado, S. Carver, C. Packer, M. Mendoza, M. E. Craft

This paper develops a machine learning framework to predict pathogen exposure in wild lions using ecological data, finding non-linear patterns and variable interactions that improve predictive performance.

bioRxiv · Mar 6, 2019Ecology