Author

Ryan M. Carney

University of South FloridaORCID 0000-0002-5537-5366Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Ecology· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:imaging· 1 Organism:multiple species· 1 Approach:statistical model· 1

Frequent Co-Authors

Johnny A. UelmeniD· 2 shared Abe MegahediD· 1 shared Akihiro ItoigawaiD· 1 shared Allie Hannum· 1 shared Atsuko YamaguchiiD· 1 shared Atsuko YamashitaiD· 1 shared Borja RehiD· 1 shared Cristina RaffertyiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersEcology

Johnny A. UelmenORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Early origin of sugar sensing in jawed vertebrates

Qiaoyi Liang, Yasuka Toda, Pauline Affatato, Gentoku Kakizaki, Hitomi Kaname, Kayoko Suzuki, Tae Kuramoto, Meng‐Ching Ko, Maxime Policarpo, Julia F. Cramer, Akihiro Itoigawa, Keisuke Furumitsu, Keren R. Sadanandan, Shigehiro Kuraku, Atsuko Yamaguchi, , Maude W. Baldwin

This study investigates the evolutionary origin of sugar sensing in vertebrates, finding that it predates angiosperms and involves multiple independent T1R-based mechanisms.

bioRxiv · Aug 28, 2026 · PreprintEvolutionary Biology

Urban larval mosquito surveillance in Antananarivo, Madagascar: spatiotemporal heterogeneity and associated vector dynamics

Mbolatiana Tovo Andrianjafy, Johnny A. Uelmen, Lala Sahondra Rafarasoa, Ranto N. Rasolofo, Mamisoa A. Ramahazomanana, Cristina Rafferty, Sarah Zohdy, Ryan M. Carney

This study identifies larval mosquito habitats and species diversity in Antananarivo, Madagascar, revealing spatiotemporal patterns and habitat preferences of public health vectors.

bioRxiv · Jul 20, 2026 · PreprintEcology

A scutum-focused deep learning pipeline for species-level identification of Aedes aegypti and Aedes albopictus from citizen-science images

Nikhil Kruthiventi, Allie Hannum, Abe Megahed, Sriram Chellappan, Ryan M. Carney, Finn Kuusisto, Johnny A. Uelmen

The paper develops a deep learning pipeline to identify Aedes aegypti and Aedes albopictus from citizen-science images by focusing on the scutum region, achieving improved classification accuracy.

bioRxiv · May 27, 2026 · PreprintBioinformatics