Author

Yebin Ryu

Korea 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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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:scRNA-seq· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Joon‐Yong AniD· 2 shared Daekee LeeiD· 1 shared Donna M. WerlingiD· 1 shared Eunhyong Chang· 1 shared Eunjoon KimiD· 1 shared Gaeun ByeoniD· 1 shared Guiyoung BongiD· 1 shared Haeun Jung· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Joon‐Yong AnORCID

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2 papers

Recent·Most cited

AI-driven framework modeling perturbation in brain organoids reveals candidate genes for autism

In Gyeong Koh, Eunhyong Chang, Young Seok Choi, Soo-Whee Kim, Yujin Kim, Hyeji Lee, Gaeun Byeon, Yebin Ryu, Seoyeon Kim, Jihae Lee, Hayoon Park, Hwanseok Sim, Yeojin Ryu, Woojong Shim, Jiho Lee, , Joon‐Yong An

The paper uses an AI-driven framework to model perturbations in brain organoids and identifies candidate genes for autism using genomic and clinical data.

bioRxiv · Aug 26, 2026 · PreprintBioinformatics

megaMine: a scalable, rule-based framework for mining gene-cancer-drug evidence from biomedical literature

Muhammad Junaid, Karolina Hanna Prazanowska, Haeun Jung, Yebin Ryu, Jeff Choi, Joon‐Yong An, Su Bin Lim

megaMine extracts gene-cancer-drug evidence from biomedical literature using a rule-based framework, achieving high accuracy in distinguishing efficacy from non-efficacy evidence.

bioRxiv · Aug 12, 2026 · PreprintBioinformatics