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Heejoon Chae

Showing results (1-10 of 36) with videos related to

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BMC Bioinformatics|May 13, 2020
methCancer-gen: a DNA methylome dataset generator for user-specified cancer type based on conditional variational autoencoderJoungmin Choi, Heejoon Chae
BMC Bioinformatics|April 26, 2023
moBRCA-net: a breast cancer subtype classification framework based on multi-omics attention neural networksJoung Min Choi, Heejoon Chae
Peerj|November 17, 2025
TSCytoPred: a deep learning framework for inferring cytokine expression trajectories from irregular longitudinal gene expression data to enhance multi-omics analysesJoung Min Choi, Heejoon Chae
Scientific Reports|March 5, 2026
A unified framework for correcting batch effects and integrating multi-omics dataJoung Min Choi, Heejoon Chae
BMC Bioinformatics|December 12, 2018
BiSpark: a Spark-based highly scalable aligner for bisulfite sequencing dataSeokjun Soe, Yoonjae Park, Heejoon Chae
BMC Medical Genomics|June 6, 2015
Combined analysis of gene regulatory network and SNV information enhances identification of potential gene markers in mouse knockout studies with small number of samplesBenjamin Hur, Heejoon Chae, Sun Kim
Micromachines|February 27, 2026
The Evolution of Lithography: From Resolution Scaling to Manufacturing ConstraintsHeejoon Chae, Hyunje Park, Dae Joon Kang
BMC Bioinformatics|April 26, 2023
meth-SemiCancer: a cancer subtype classification framework via semi-supervised learning utilizing DNA methylation profilesJoung Min Choi, Chaelin Park, Heejoon Chae
Peerj|March 1, 2024
moSCminer: a cell subtype classification framework based on the attention neural network integrating the single-cell multi-omics dataset on the cloudJoung Min Choi, Chaelin Park, Heejoon Chae
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|June 10, 2026
Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised LearningChaelin Park, Joung Min Choi, Heejoon Chae
Pageof 4

Showing results (1-10 of 36) with videos related to

Sort By:
Pageof 4
BMC Bioinformatics|May 13, 2020
methCancer-gen: a DNA methylome dataset generator for user-specified cancer type based on conditional variational autoencoderJoungmin Choi, Heejoon Chae
BMC Bioinformatics|April 26, 2023
moBRCA-net: a breast cancer subtype classification framework based on multi-omics attention neural networksJoung Min Choi, Heejoon Chae
Peerj|November 17, 2025
TSCytoPred: a deep learning framework for inferring cytokine expression trajectories from irregular longitudinal gene expression data to enhance multi-omics analysesJoung Min Choi, Heejoon Chae
Scientific Reports|March 5, 2026
A unified framework for correcting batch effects and integrating multi-omics dataJoung Min Choi, Heejoon Chae
BMC Bioinformatics|December 12, 2018
BiSpark: a Spark-based highly scalable aligner for bisulfite sequencing dataSeokjun Soe, Yoonjae Park, Heejoon Chae
BMC Medical Genomics|June 6, 2015
Combined analysis of gene regulatory network and SNV information enhances identification of potential gene markers in mouse knockout studies with small number of samplesBenjamin Hur, Heejoon Chae, Sun Kim
Micromachines|February 27, 2026
The Evolution of Lithography: From Resolution Scaling to Manufacturing ConstraintsHeejoon Chae, Hyunje Park, Dae Joon Kang
BMC Bioinformatics|April 26, 2023
meth-SemiCancer: a cancer subtype classification framework via semi-supervised learning utilizing DNA methylation profilesJoung Min Choi, Chaelin Park, Heejoon Chae
Peerj|March 1, 2024
moSCminer: a cell subtype classification framework based on the attention neural network integrating the single-cell multi-omics dataset on the cloudJoung Min Choi, Chaelin Park, Heejoon Chae
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|June 10, 2026
Cell Type Prediction for Single-Cell RNA Sequencing Utilizing Unsupervised Domain Adaptation and Semi-Supervised LearningChaelin Park, Joung Min Choi, Heejoon Chae
Pageof 4