Author

Hyung‐Jun Im

Seoul National UniversityORCID 0000-0002-4368-6685Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:spatial transcriptomics· 4 Research Focus:cell type annotation· 3 Organism:human· 3 Approach:statistical model· 3 Research Focus:cell-cell communication· 2 Research Focus:differential expression· 2 Approach:experimental assay· 2 Approach:deep learning· 1

Frequent Co-Authors

Hongyoon ChoiiD· 5 shared Jeongbin ParkiD· 4 shared Daeseung LeeiD· 3 shared Dongjoo LeeiD· 3 shared Jae Eun LeeiD· 2 shared Jinyeong ChoiiD· 2 shared Kwon Joong NaiD· 2 shared Hyun Soo ParkiD· 1 shared

Activity by Year

2021-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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5 shared papersBioinformatics

Hongyoon ChoiORCID

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5 papers

Recent·Most cited

Spatial Transcriptomics Reveals Spatially Diverse Cancer-Associated Fibroblast in Lung Squamous Cell Carcinoma Linked to Tumor Progression

Hongyoon Choi, Kwon Joong Na, Yeonjae Jung, Myunghyun Lim, Dongjoo Lee, Jae Eun Lee, Hyung‐Jun Im, Daeseung Lee, Jaemoon Koh, Young Tae Kim

This study uses spatial transcriptomics to analyze cancer-associated fibroblasts in lung squamous cell carcinoma, linking their spatial organization to tumor progression and patient outcomes.

bioRxiv · May 16, 2024 · PreprintCancer Biology

A Spatial Transcriptomics based Label-Free Method for Assessment of Human Stem Cell Distribution and Effects in a Mouse Model of Lung Fibrosis

Jeongbin Park, Dongjoo Lee, Jae Eun Lee, Daeseung Lee, In Ho Song, Hyun Soo Park, Hongyoon Choi, Hyung‐Jun Im

Advanced Therapeutics · Jan 24, 2024Peer-reviewedBioinformatics

Generation of Super-resolution Images from Barcode-based Spatial Transcriptomics Using Deep Image Prior

Jeongbin Park, Seungho Cook, Dongjoo Lee, Jinyeong Choi, Seongjin Yoo, Hyung‐Jun Im, Daeseung Lee, Hongyoon Choi

This paper introduces SuperST, a deep learning method that reconstructs high-resolution spatial gene expression images from low-resolution barcode-based spatial transcriptomics data, improving alignment with immunofluorescence images.

bioRxiv · Jun 26, 2023 · PreprintBioinformatics

Spatial Transcriptomics-based Identification of Molecular Markers for Nanomedicine Distribution in Tumor Tissue

Jeongbin Park, Jinyeong Choi, Jae Eun Lee, Hongyoon Choi, Hyung‐Jun Im

The paper identifies molecular markers associated with nanomedicine distribution in tumor tissue using spatial transcriptomics and fluorescence imaging.

Small Methods · Sep 30, 2022Peer-reviewedBioinformatics

Discovery of potential imaging and therapeutic targets for severe inflammation in COVID-19 patients

Hyun‐Jong Lee, Jeongbin Park, Hyung‐Jun Im, Kwon Joong Na, Hongyoon Choi

The paper identifies potential imaging and therapeutic targets for severe COVID-19 inflammation by analyzing single-cell RNA-seq data from patient samples.

Scientific Reports · Jul 8, 2021Peer-reviewedBioinformatics