Author

Jiwon Kim

Amazon (United States)ORCID 0000-0001-7515-0837Unclaimed ORCID profile · follow to get notified of new preprints

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Jiwon Kim2 papers · Augusta University

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:spatial transcriptomics· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:database / resource· 1

Frequent Co-Authors

Hongyoon ChoiiD· 2 shared Jeongbin ParkiD· 2 shared Chuanyui Teh· 1 shared Daeseung LeeiD· 1 shared Dongjoo LeeiD· 1 shared Edward LeeiD· 1 shared Eun‐Jae ChungiD· 1 shared Fangda XuiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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2 shared papersBioinformatics

Hongyoon ChoiORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintApr 17, 2026

Agent-Guided De Novo Design of Nanobody Binders Against a Novel Cancer Target

Yue Zhao, Melih Yilmaz, Edward Lee…·Xinyun Cheng

The paper presents a computational workflow for designing nanobody binders against a novel cancer target, achieving sub-nanomolar affinities without experimental structure or prior antibody data.

DOI 10.64898/2026.04.13.717816

humanprotein sequence

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BioinformaticsbioRxivPreprintJun 9, 2024

Analysis of Unmapped RNA-seq Data from Cancer Spatial Transcriptome to Decipher Cancer Microbiome

Seo Hye Park, Jeongbin Park, Jiwon Kim…·Kwon Joong Na

The paper analyzes unmapped RNA-seq data from cancer spatial transcriptomes to study microbial RNA distribution and function in cancer tissues.

DOI 10.1101/2024.06.09.598160

humanspatial transcriptomics

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BioinformaticsbioRxivPreprintMay 8, 2024

CELLama: Foundation Model for Single Cell and Spatial Transcriptomics by Cell Embedding Leveraging Language Model Abilities

Hongyoon Choi, Jeongbin Park, Sumin Kim…·Daeseung Lee

CELLama transforms single-cell and spatial transcriptomics data into embeddings using language model abilities, enabling flexible analysis without manual reference data.

13 citations

scRNA-seqspatial transcriptomics

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