Author

Junho Chung

Seoul National UniversityORCID 0000-0003-4873-8031Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Assay:CITE-seq· 1 Research Focus:clustering· 1 Assay:proteomics· 1

Frequent Co-Authors

Byung‐Gee KimiD· 1 shared Eunjae LeeiD· 1 shared Ha Young ShiniD· 1 shared Hyunho LeeiD· 1 shared Inyoung KimiD· 1 shared Jinsung NohiD· 1 shared Jong Hoon KimiD· 1 shared Kyoungseob ShiniD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperBioinformatics

Byung‐Gee KimORCID

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2 papers

Recent·Most cited

BioinformaticsFrontiers in ImmunologyPeer-reviewedMar 21, 2024

Identification of B cell subsets based on antigen receptor sequences using deep learning

Hyunho Lee, Kyoungseob Shin, Yong‐Ju Lee…·Sunghoon Kwon

This paper introduces BCR-SORT, a deep learning model that predicts B cell subsets from BCR sequences, revealing inter-individual heterogeneity in memory B cell evolution post-COVID-19 vaccination.

5 citations

humanCITE-seq

𝕏 PostBluesky

BioinformaticsbioRxivPreprintAug 2, 2021

Computational analysis of B cell receptor repertoires in COVID-19 patients using deep embedded representations of protein sequences

Inyoung Kim, Sang Yoon Byun, Sangyeup Kim…·Byung‐Gee Kim

This paper introduces a deep learning-based method to analyze B cell receptor repertoires in COVID-19 patients and healthy subjects, enabling accurate clustering and classification of immune status changes.

2 citations

humanproteomics

𝕏 PostBluesky