Author

H. Ferte

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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Microbiology· 2 Physiology· 1

Signature Assays, Organisms & Methods

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Research Focus:host-pathogen & immune response· 2 Research Focus:cell type annotation· 1 Approach:experimental assay· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Organism:multiple species· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

J. Depaquit· 2 shared A. Huguenin· 1 shared A.-B. Failloux· 1 shared B. D. Rey· 1 shared B. Mathieu· 1 shared C. Bohers· 1 shared C. Peroz· 1 shared E. Gilot-Fromont· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersMicrobiology

J. Depaquit

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Early-life glucocorticoids accelerate lymphocyte count senescence in roe deer

L. D. Lalande, G. Bourgoin, J. Carbillet, L. Cheynel, F. Debias, H. Ferte, J.-M. Gaillard, R. Garcia, J.-F. Lemaitre, R. Palme, M. Pellerin, C. Peroz, B. D. Rey, P. Vuarin, E. Gilot-Fromont

This study shows that high early-life glucocorticoid levels in roe deer accelerate lymphocyte decline and increase adult parasite susceptibility.

bioRxiv · May 24, 2024Physiology

Assessing vector competence of mosquitoes from northeastern France to West Nile virus and Usutu virus

J.-P. Martinet, C. Bohers, M. Vazeille, H. Ferte, L. Mousson, B. Mathieu, J. Depaquit, A.-B. Failloux

The paper assesses the vector competence of five mosquito species in northeastern France for West Nile virus and Usutu virus, finding that Culex pipiens and Aedes albopictus can transmit both viruses.

bioRxiv · Feb 7, 2023 · PreprintMicrobiology

MALDI-TOF : A new tool for the identification of Schistosoma cercariae and detection of hybrids

A. Huguenin, J. Kincaid-Smith, J. Depaquit, J. Boissier, H. Ferte

This paper evaluates MALDI-TOF for identifying Schistosoma cercariae and detecting hybrids, achieving 94% accuracy with machine learning improving discrimination between hybrids and S. haematobium.

bioRxiv · Jun 14, 2022Microbiology