Author

Jessica E. Heebner

Pennsylvania 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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Cell Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Assay:cryo-EM· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:comparative / phylogenetic analysis· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Approach:microscopy & imaging analysis· 1

Frequent Co-Authors

Matthew T. SwuliusiD· 2 shared Carrie L. ShafferiD· 1 shared Carson J. PurnelliD· 1 shared Erich Raumann· 1 shared Frederick A. HeberleiD· 1 shared Jason L. RasgoniD· 1 shared Linh Nguyen· 1 shared M. Neal WaxhamiD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersMicrobiology

Matthew T. SwuliusORCID

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2 papers

Recent·Most cited

In situ architecture of the endosymbiont Wolbachia pipientis

Sujit Kumar Pujhari, Jessica E. Heebner, Erich Raumann, Tengfei Zhong, Jason L. Rasgon, Matthew T. Swulius, Carrie L. Shaffer, Mohammed Kaplan

This study uses cryo-electron tomography to reveal the nanoscale architecture of Wolbachia pipientis structures involved in host manipulation and maternal inheritance.

bioRxiv · Aug 29, 2025 · PreprintMicrobiology

Training Generalized Segmentation Networks with Real and Synthetic Cryo-ET data.

Carson J. Purnell, Jessica E. Heebner, Linh Nguyen, Michael T. Swulius, Ryan K. Hylton, Seth G. Kabonick, Michael A. Grillo, Stephanie L. Grillo, Sergei A. Grigoryev, Frederick A. Heberle, M. Neal Waxham

The paper trains segmentation networks for cryo-ET data using synthetic and real data, showing that synthetic data with molecular diversity improves performance but real data is needed for generalization.

bioRxiv · Jan 31, 2025 · PreprintCell Biology