Author

J. D. Aponte

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:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:dimensionality reduction· 1 Organism:mouse· 1 Approach:statistical model· 1

Frequent Co-Authors

B. Hallgrimsson· 1 shared C. J. Percival· 1 shared D. C. Katz· 1 shared D. Houle· 1 shared F. H. Rodd· 1 shared J. Devine· 1 shared J. J. Valvo· 1 shared K. A. Hughes· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperEvolutionary Biology

B. Hallgrimsson

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2 papers

Recent·Most cited

Colormesh: A novel method for quantifying variation in complex color patterns

J. J. Valvo, F. H. Rodd, J. D. Aponte, M. Daniel, K. Dwinell, D. Houle, K. A. Hughes

Colormesh quantifies color pattern variation by maintaining continuous color measures across sampling points, avoiding categorical reductions and spatial information loss.

bioRxiv · Jul 17, 2020 · PreprintEvolutionary Biology

A Registration and Deep Learning Approach to Automated Landmark Detection for Geometric Morphometrics

J. Devine, J. D. Aponte, D. C. Katz, W. Liu, L. D. Lo Vercio, N. D. Forkert, C. J. Percival, B. Hallgrimsson

This paper develops a method combining image registration and deep learning to automate landmark detection for geometric morphometrics, showing significant error reduction compared to manual methods.

bioRxiv · Dec 11, 2019Evolutionary Biology