Author

J. L. Gage

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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Plant Biology· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Assay:imaging· 1 Organism:plant (other)· 1 Approach:statistical model· 1

Frequent Co-Authors

B. Alaca· 1 shared C. N. Hirsch· 1 shared C. Soman· 1 shared D. C. Lima· 1 shared D. Ertl· 1 shared D. Kick· 1 shared D. Moreta· 1 shared E. Richards· 1 shared

Activity by Year

2019-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperPlant Biology

B. Alaca

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2 papers

Recent·Most cited

Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning

D. Kick, J. Wallace, J. C. Schnable, J. M. Kolkman, B. Alaca, T. M. Beissinger, D. Ertl, S. Flint-Garcia, J. L. Gage, C. N. Hirsch, J. E. Knoll, N. de Leon, D. C. Lima, D. Moreta, M. Singh, , J. D. Washburn

This study uses deep learning to predict maize yield by integrating genetic, environmental, and management data, finding that models incorporating interactions perform best.

bioRxiv · Jul 29, 2022Plant Biology

In-field whole plant maize architecture characterized by Latent Space Phenotyping

J. L. Gage, E. Richards, N. Lepak, N. Kaczmar, C. Soman, G. Chowdhary, M. A. Gore, E. S. Buckler

This study uses LiDar and Latent Space Phenotyping to extract quantitative plant architecture traits from maize fields, showing heritability and predictive power for breeding and research.

bioRxiv · Sep 10, 2019Plant Biology