Author

Donggeon Lee

Sungkyunkwan University School of Medicine;Primary ORCID profile (0009-0006-2716-156X · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Same name, identified by ORCID

Donggeon LeeiD1 paper · Samsung (South Korea)

Biology Disciplines

Click to filter author papers

Bioinformatics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Eunae Sandra Cho· 1 shared Hanjae Lee· 1 shared Heetak LeeiD· 1 shared Hyeon-Min KimiD· 1 shared Jeongbin ParkiD· 1 shared Jong-Il KimiD· 1 shared Junseong Bae· 1 shared Ohsang Kwon· 1 shared

Activity by Year

2026-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperBioinformatics

Eunae Sandra Cho

Mutual co-authors in cluster

Author profile →

1 paper

Recent·Most cited

Agentic AI enables cell segmentation-free cell-type inference and cell-type-guided cell segmentation in spatial transcriptomics

Yuhui Jeong, Hanjae Lee, Donggeon Lee, Hyeon-Min Kim, So-Hui Kim, Suhyeon Park, Junseong Bae, Eunae Sandra Cho, Yoon-La Choi, Ohsang Kwon, Jong-Il Kim, Heetak Lee, Jeongbin Park

This paper introduces SSAF-T, a segmentation-free framework for cell-type inference in spatial transcriptomics that avoids cell segmentation and enables accurate cell-type-guided segmentation.

bioRxiv · Nov 6, 2026 · PreprintBioinformatics