EGGSlicer: predicting biologically meaningful gene sets from gene clusters using gene ontology information. - Heejoon Chae; Kwangmin Choi; Sun Kim; Haleh Ashki (BCB, 2010)

BioVLAB-MMIA: A Reconfigurable Cloud Computing Environment for microRNA and mRNA Integrated Analysis. - Hyungro Lee; Youngik Yang; Heejoon Chae; Seungyoon Nam; Donghoon Choi; Patanachai Tangchaisin; Chathura Herath; Suresh Marru; Kenneth P. Nephew; Sun Kim (BIBM, 2011)

Transitioning BioVLab cloud workbench to a science gateway. - Suresh Marru; Heejoon Chae; Patanachai Tangchaisin; Sun Kim; Marlon E. Pierce; Kenneth P. Nephew (TG, 2011)

Bio and health informatics meets cloud : BioVLab as an example. - Heejoon Chae; Inuk Jung; Hyungro Lee; Suresh Marru; Seong-Whan Lee; Sun Kim (Health Inf. Sci. Syst., 2013)

Genome-Wide Analysis and Modeling of DNA methylation susceptibility in 30 Breast Cancer Cell Lines by using CPG Flanking Sequences. - Jaehyun An; Kwangsoo Kim; SungMin Rhee; Heejoon Chae; Kenneth P. Nephew; Sun Kim (J. Bioinform. Comput. Biol., 2013)

BioVLAB-MMIA-NGS: microRNA-mRNA integrated analysis using high-throughput sequencing data. - Heejoon Chae; SungMin Rhee; Kenneth P. Nephew; Sun Kim (Bioinform., 2015)

Subtype-specific CpG island shore methylation and mutation patterns in 30 breast cancer cell lines. - Heejoon Chae; Sangseon Lee; Kenneth P. Nephew; Sun Kim (BMC Syst. Biol., 2016)

Integration of heterogeneous time series gene expression data by clustering on time dimension. - Hongryul Ahn; Heejoon Chae; Woosuk Jung; Sun Kim (BigComp, 2017)

HTRgene: Integrating Multiple Heterogeneous Time-series Data to Investigate Cold and Heat Stress Response Signaling Genes in Arabidopsis. - Hongryul Ahn; Inuk Jung; Heejoon Chae; Dongwon Kang; Woosuk Jung; Sun Kim (BIBM, 2018)

BiSpark: a Spark-based highly scalable aligner for bisulfite sequencing data. - Seokjun Soe; Yoonjae Park; Heejoon Chae (BMC Bioinform., 2018)

Cloud-BS: A MapReduce-based bisulfite sequencing aligner on cloud. - Joungmin Choi; Yoonjae Park; Sun Kim; Heejoon Chae (J. Bioinform. Comput. Biol., 2018)

HTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in Arabidopsis. - Hongryul Ahn; Inuk Jung; Heejoon Chae; Dongwon Kang; Woosuk Jung; Sun Kim (BMC Bioinform., 2019)

A Non-Negative Matrix Factorization-Based Framework for the Analysis of Multi-Class Time-Series Single-Cell RNA-Seq Data. - Inuk Jung; Joungmin Choi; Heejoon Chae (IEEE Access, 2020)

methCancer-gen: a DNA methylome dataset generator for user-specified cancer type based on conditional variational autoencoder. - Joungmin Choi; Heejoon Chae (BMC Bioinform., 2020)

IDEA: Integrating Divisive and Ensemble-Agglomerate hierarchical clustering framework for arbitrary shape data. - Hongryul Ahn; Inuk Jung; Heejoon Chae; Minsik Oh; Inyoung Kim; Sun Kim (IEEE BigData, 2021)

Cell Subtype Classification via Representation Learning Based on a Denoising Autoencoder for Single-Cell RNA Sequencing. - Joungmin Choi; Je-Keun Rhee; Heejoon Chae (IEEE Access, 2021)

Correction to "A Non-Negative Matrix Factorization Based Framework for the Analysis of Multi-Class Time-Series Single-Cell RNA-Seq Data". - Inuk Jung; Joungmin Choi; Heejoon Chae (IEEE Access, 2021)

Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations. - Minsik Oh; Sungjoon Park; Sun Kim; Heejoon Chae (Briefings Bioinform., 2021)

Erratum to: Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations. - Minsik Oh; Sungjoon Park; Sun Kim; Heejoon Chae (Briefings Bioinform., 2021)

BioVLAB-Cancer-Pharmacogenomics: tumor heterogeneity and pharmacogenomics analysis of multi-omics data from tumor on the cloud. - Sungjoon Park; Dohoon Lee; Youngkuk Kim; Sangsoo Lim; Heejoon Chae; Sun Kim (Bioinform., 2021)

moBRCA-net: a breast cancer subtype classification framework based on multi-omics attention neural networks. - Joung Min Choi; Heejoon Chae (BMC Bioinform., 2023)

meth-SemiCancer: a cancer subtype classification framework via semi-supervised learning utilizing DNA methylation profiles. - Joung Min Choi; Chaelin Park; Heejoon Chae (BMC Bioinform., 2023)