Author

Elyse Vischulis

Michigan State University

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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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Organism:Arabidopsis· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Eamon F. WinshipiD· 1 shared Fanrui MengiD· 1 shared Jeffrey K. ConneriD· 1 shared Melissa D. Lehti‐ShiuiD· 1 shared Nicholas L. PanchyiD· 1 shared Paityn Donaldson· 1 shared Patrick J. KrysaniD· 1 shared Peipei WangiD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Eamon F. WinshipORCID

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1 paper

Recent·Most cited

High throughput measurement of Arabidopsis thaliana fitness traits using deep learning

Peipei Wang, Fanrui Meng, Paityn Donaldson, Sarah Horan, Nicholas L. Panchy, Elyse Vischulis, Eamon F. Winship, Jeffrey K. Conner, Patrick J. Krysan, Shin‐Han Shiu, Melissa D. Lehti‐Shiu

This study uses deep learning to accurately measure Arabidopsis fitness traits, revealing gene function effects previously undetected by traditional methods.

New Phytologist · Feb 25, 2022Peer-reviewedBioinformatics