Author

E. C. Teeling

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 Evolutionary Biology· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Organism:mouse· 3 Research Focus:host-pathogen & immune response· 2 Organism:human· 2 Organism:rat· 2 Assay:bulk RNA-seq· 1 Approach:comparative / phylogenetic analysis· 1 Organism:multiple species· 1

Frequent Co-Authors

S. J. Puechmaille· 2 shared A. A. Kolodziejczyk· 1 shared A. R. Sjodin· 1 shared B. A. Han· 1 shared C. J. Carlson· 1 shared C. Stragier· 1 shared D. Becker· 1 shared E. A. Eskew· 1 shared

Activity by Year

2020-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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2 shared papersEvolutionary Biology

S. J. Puechmaille

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

A comparative analysis of the antiviral response in two bat species reveals conserved and divergent innate immune pathways

L. Schneor, S. Kaltenbach, S. Fridman, Y. Nissan, G. Shuler, E. Fraimovitch, M. Weinberg, A. A. Kolodziejczyk, G. Donati, E. C. Teeling, Y. Yovel, T. Hagai

This study compares antiviral responses in two bat species, finding conserved gene upregulation and divergent transcriptional patterns linked to viral tolerance and resistance.

bioRxiv · Apr 23, 2023 · PreprintEvolutionary Biology

Comparative genome microsynteny illuminates the fast evolution of nuclear mitochondrial segments (NUMTs) in mammals

M. Uvizl, S. J. Puechmaille, S. Power, M. Pippel, S. Carthy, W. Haerty, E. W. Myers, E. C. Teeling, Z. Huang

This study investigates NUMT evolution across 45 mammalian genomes using synteny-based methods, revealing their origin patterns and phylogenetic implications.

bioRxiv · Apr 20, 2023Evolutionary Biology

Mark loss can strongly bias demographic rates in multi-state models: a case study with simulated and empirical datasets

F. Touzalin, E. J. Petit, E. Cam, C. Stragier, E. C. Teeling, S. J. Puechmaille

This study shows mark loss can bias demographic estimates in multi-state models, using simulations and bat data to demonstrate the impact and mitigation strategies.

bioRxiv · Mar 25, 2022Ecology

Optimizing predictive models to prioritize viral discovery in zoonotic reservoirs

D. Becker, G. F. Albery, A. R. Sjodin, T. Poisot, L. Bergner, T. Dallas, E. A. Eskew, M. J. Farrell, S. Guth, B. A. Han, N. B. Simmons, M. Stock, E. C. Teeling, C. J. Carlson

This study compares and validates predictive models to prioritize sampling of bat hosts for betacoronaviruses, finding ecological trait-based models outperform network methods.

bioRxiv · May 22, 2020Ecology