Author

F. A. N. Fernandes

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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Evolutionary Biology· 3 Ecology· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Research Focus:chromatin & epigenetic regulation· 2 Organism:multiple species· 2 Organism:non-human primate· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Approach:comparative / phylogenetic analysis· 1 Approach:deep learning· 1

Frequent Co-Authors

C. Le Bohec· 4 shared E. Trucchi· 4 shared F. Pirri· 2 shared L. Ancona· 2 shared L. Zane· 2 shared M. Benoiste· 2 shared A. Houstin· 1 shared A. Krellenstein· 1 shared

Activity by Year

2021-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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4 shared papersEvolutionary Biology

C. Le Bohec

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Author profile →

4 papers

Recent·Most cited

Gene expression shifts in Emperor penguin adaptation to the extreme Antarctic environment

J. R. Paris, F. A. N. Fernandes, F. Pirri, S. Greco, M. Gerdol, A. Pallavicini, M. Benoiste, C. Cornec, L. Zane, B. Haas, C. Le Bohec, E. Trucchi

This study compares gene expression in Emperor and King penguins to identify adaptations to extreme Antarctic environments, finding key roles for muscle and liver in metabolism and regulatory shifts in the brain.

bioRxiv · Nov 29, 2023Evolutionary Biology

Gene expression is the main driver of purifying selection in large penguin populations

E. Trucchi, P. Massa, F. Giannelli, T. Latrille, F. A. N. Fernandes, L. Ancona, N. C. Stenseth, J. Ferrer Obiol, J. Paris, G. Bertorelle, C. Le Bohec

The paper shows gene expression drives purifying selection in penguin populations, with highly expressed genes experiencing stronger selection pressures.

bioRxiv · Aug 8, 2023 · PreprintEvolutionary Biology

RFIDeep: Unfolding the Potential of Deep Learning forRadio-Frequency Identification

G. Bardon, R. Cristofari, A. Winterl, T. Barracho, M. Benoiste, C. Ceresa, N. Chatelain, J. Courtecuisse, F. A. N. Fernandes, M. Gauthier-Clerc, J.-P. Gendner, Y. Handrich, A. Houstin, A. Krellenstein, N. Lecomte, , C. Le Bohec

RFIDeep uses deep learning to analyze RFID mark-recapture data and accurately determine breeding status, phenology, and success in seabirds.

bioRxiv · Mar 25, 2023Ecology

Selection-driven adaptation to the extreme Antarctic environment in the Emperor penguin

F. Pirri, L. Ometto, S. Fuselli, F. A. N. Fernandes, L. Ancona, C. Le Bohec, L. Zane, E. Trucchi

This study identifies genomic signatures of selection in Emperor and King penguins to determine if Emperor penguin's cold adaptation evolved from a more King penguin-like ancestor.

bioRxiv · Dec 14, 2021Evolutionary Biology