Author

Marilyn Lionts

Vanderbilt UniversityORCID 0000-0002-9889-3390Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:software / tool· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Yuankai HuoiD· 2 shared Alec B. WalteriD· 1 shared Andrea K. LockeiD· 1 shared Anita M. Mahadevan-JanseniD· 1 shared Chongyu QuiD· 1 shared Daguang XuiD· 1 shared Ezekiel J. HaugeniD· 1 shared George Grow· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBioengineering

Yuankai HuoORCID

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2 papers

Recent·Most cited

TRaP: An Open-source, Reproducible Framework for Raman Spectral Preprocessing across Heterogeneous Systems

Yanfan Zhu, Marilyn Lionts, Ezekiel J. Haugen, Alec B. Walter, Trevor Voss, George Grow, Ruo-Yin Liao, Meagan E. McKee, Rafay Ahmed, Joseph K. Afreh, Andrea K. Locke, Girish S Hiremath, Anita M. Mahadevan-Jansen, Yuankai Huo

TRaP provides an open-source framework for reproducible Raman spectral preprocessing across different systems, enabling consistent and transparent analysis workflows.

bioRxiv · Jun 2, 2026 · PreprintBioengineering

Computer Vision Methods for Spatial Transcriptomics: A Survey

Junchao Zhu, Ruining Deng, Junlin Guo, Tianyuan Yao, Siqi Lu, Chongyu Qu, Juming Xiong, Yanfei Zhu, Zhengyi Lu, Yuechen Yang, Marilyn Lionts, Yucheng Tang, Daguang Xu, Yu Wang, Shilin Zhao, , Yuankai Huo

This paper surveys computer vision methods for spatial transcriptomics, categorizing models and discussing challenges and future directions.

bioRxiv · Oct 13, 2025 · PreprintBioinformatics