Author

L. Flagel

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· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:whole-genome sequencing· 2 Research Focus:cell type annotation· 1 Organism:Drosophila· 1 Research Focus:gene regulatory network inference· 1 Research Focus:phylogenetics / evolution· 1 Approach:transformer / foundation model· 1 Research Focus:variant calling· 1

Frequent Co-Authors

D. R. Schrider· 2 shared D. D. Ray· 1 shared Y. J. Brandvain· 1 shared

Activity by Year

2018-2024 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 2 mutual co-author links

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2 shared papersEvolutionary Biology

D. R. Schrider

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2 papers

Recent·Most cited

IntroUNET: identifying introgressed alleles via semantic segmentation

D. D. Ray, L. Flagel, D. R. Schrider

This paper introduces IntroUNET, a deep learning method for identifying introgressed alleles using semantic segmentation, showing high accuracy in simulated and real data from Drosophila.

PLOS Genetics · Feb 20, 2024Peer-reviewedEvolutionary Biology

The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference

L. Flagel, Y. J. Brandvain, D. R. Schrider

This paper applies convolutional neural networks to population genetic inference, showing they match or exceed current methods in accuracy and model selection.

bioRxiv · Nov 27, 2018Evolutionary Biology