Author

E. Shane

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 Bioengineering· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Assay:imaging· 2 Organism:Arabidopsis· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

A. Ai-Perreira· 1 shared A. B. Rajurkar· 1 shared A. Cohen· 1 shared A. J. Bloom· 1 shared A. Knapp· 1 shared A. Talgo· 1 shared B. Aeppli· 1 shared C. Bregoli· 1 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperPlant Biology

A. Ai-Perreira

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Author profile →

3 papers

Recent·Most cited

Fast and efficient root phenotyping via pose estimation

E. M. Berrigan, L. Wang, H. Carrillo, K. Echegoyen, M. Kappes, J. Torres, A. Ai-Perreira, E. McCoy, E. Shane, C. D. Copeland, L. Ragel, C. Georgousakis, S. Lee, D. Reynolds, A. Talgo, , T. D. Pereira

This paper introduces a segmentation-free root phenotyping method using pose estimation, showing high accuracy and efficiency compared to segmentation-based approaches.

bioRxiv · Nov 20, 2023Plant Biology

Differential genetic variation underlying Ammonium and Nitrate responses in Arabidopsis thaliana

E. Katz, A. Knapp, M. Lensink, J. Stefani, J.-J. Li, E. Shane, K. Tuermer-Lee, A. J. Bloom, D. J. Kliebenstein

The paper identifies a large number of genes involved in Arabidopsis thaliana's nitrogen response by analyzing natural genotypes under different nitrogen sources.

bioRxiv · Apr 27, 2022Plant Biology

Large-scale quantification of human osteocyte lacunar morphological biomarkers as assessed by ultra-high-resolution desktop micro-computed tomography

E. Goff, F. Buccino, C. Bregoli, J. P. McKinley, B. Aeppli, R. R. Recker, E. Shane, A. Cohen, G. Kuhn, R. Müller

This study assesses the accuracy, reproducibility, and sensitivity of ultra-high-resolution desktop micro-CT for large-scale quantification of human osteocyte lacunar morphometry in clinical biopsies.

bioRxiv · Jan 5, 2021Bioengineering