Author

Hyeonjin Cha

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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Bioengineering· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Approach:experimental assay· 1 Assay:protein structure· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Changsoo LeeiD· 2 shared Chaok SeokiD· 2 shared Daehyeon Gwak· 2 shared Deok Hyang Sa· 2 shared Hyeonuk WooiD· 2 shared Jeonghyeon GuiD· 2 shared Jinsol YangiD· 2 shared Jinsung NohiD· 2 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioengineering

Changsoo LeeORCID

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2 papers

Recent·Most cited

Precision at Every Scale: Efficiency in AI-Driven De Novo Antibody Design

Hyeonjin Cha, Kyesoo Cho, Jeonghyeon Gu, Daehyeon Gwak, Seung Woo Ham, Mirim Hong, Sehan Kim, Suyeon Kim, Sohee Kwon, Changsoo Lee, Dohoon Lee, Danyeong Lee, Dohoon Lee, Jungsub Lim, Jinsung Noh, , Jinsol Yang

This paper evaluates GaluxDesign, an AI platform, for de novo antibody design, showing a 10.5% binder rate and strong performance on benchmark targets.

bioRxiv · Nov 21, 2025 · PreprintBioengineering

Precise, Specific, and Sensitive De Novo Antibody Design Across Multiple Cases

Yewon Bang, Hyeonjin Cha, Kyesoo Cho, Jeonghyeon Gu, Daehyeon Gwak, Young-Hyun Han, Mirim Hong, Suyeon Kang, Sohee Kwon, Changsoo Lee, Do Hoon Lee, Myeong Sup Lee, Sangchoon Lee, Jungsub Lim, Jin Young Maeng, , Min Ji Yoon

This study designs antibodies without prior information across eight targets, achieving high precision, sensitivity, and specificity, validated by Cryo-EM and comparable to commercial antibodies.

bioRxiv · Mar 9, 2025 · PreprintBioengineering