Author

Danyeong Lee

Seoul National 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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Bioengineering· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Assay:protein structure· 1 Assay:whole-genome sequencing· 1 Organism:yeast· 1

Frequent Co-Authors

Dohoon LeeiD· 2 shared Aayush Prakash· 1 shared Abdul Muntakim RafiiD· 1 shared Andigoni MalousiiD· 1 shared Andreas Fønss MølleriD· 1 shared Andrey S. Lando· 1 shared Arsenii O. ZinkevichiD· 1 shared Ashley BabjaciD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioengineering

Dohoon LeeORCID

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Author profile →

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

Evaluation and optimization of sequence-based gene regulatory deep learning models

Abdul Muntakim Rafi, Daria Nogina, Dmitry Penzar, Dohoon Lee, Danyeong Lee, N. S. KIM, Sangyeup Kim, Dohyeon Kim, Yeojin Shin, Il‐Youp Kwak, Georgy Meshcheryakov, Andrey S. Lando, Arsenii O. Zinkevich, Byeongchan Kim, Juhyun Lee, , Carl G. de Boer

The paper evaluates and optimizes sequence-based gene regulatory deep learning models using a DREAM Challenge dataset, showing improvements through architectural and training strategy refinements.

Nature Biotechnology · Oct 11, 2024Peer-reviewedGenomics