BioInCode Lab AI for Bio & Medical Innovations

Research

Highlighted

Cancer subtype classification and modeling by pathway attention and propagation
Cancer subtype classification and modeling by pathway attention and propagation
Sangseon Lee, Sangsoo Lim, Taeheon Lee, Inyoung Sung, Sun Kim
Bioinformatics  ·  24 Mar 2020  ·  doi:10.1093/bioinformatics/btaa203
CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction
CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction
Hyukjun Lim, Sun Kim, Sangseon Lee
ICLR 2025  ·  24 Apr 2025  ·  [no id info]

All

2025

CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction
CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction
Hyukjun Lim, Sun Kim, Sangseon Lee
ICLR 2025  ·  24 Apr 2025  ·  [no id info]
MDTR: a knowledge-guided interpretable representation for quantifying liver toxicity at transcriptomic level
MDTR: a knowledge-guided interpretable representation for quantifying liver toxicity at transcriptomic level
Inyoung Sung, Sangseon Lee, Dongmin Bang, Jungseob Yi, Sunho Lee, Sun Kim
Frontiers in Pharmacology  ·  24 Jan 2025  ·  doi:10.3389/fphar.2024.1398370

2024

Multi-layered knowledge graph neural network reveals pathway-level agreement of three breast cancer multi-gene assays
Multi-layered knowledge graph neural network reveals pathway-level agreement of three breast cancer multi-gene assays
Sangseon Lee, Joonhyeong Park, Yinhua Piao, Dohoon Lee, Danyeong Lee, Sun Kim
Computational and Structural Biotechnology Journal  ·  01 Dec 2024  ·  doi:10.1016/j.csbj.2024.04.038
ChemAP: predicting drug approval with chemical structures before clinical trial phase by leveraging multi-modal embedding space and knowledge distillation
ChemAP: predicting drug approval with chemical structures before clinical trial phase by leveraging multi-modal embedding space and knowledge distillation
Changyun Cho, Sangseon Lee, Dongmin Bang, Yinhua Piao, Sun Kim
Scientific Reports  ·  03 Oct 2024  ·  doi:10.1038/s41598-024-72868-0
Improving out-of-distribution generalization in graphs via hierarchical semantic environments
Improving out-of-distribution generalization in graphs via hierarchical semantic environments
Yinhua Piao, Sangseon Lee, Yijingxiu Lu, Sun Kim
CVPR 2024  ·  17 Jun 2024  ·  doi:10.48550/ARXIV.2403.01773
Dual Representation Learning for Predicting Drug-side Effect Frequency using Protein Target Information
Dual Representation Learning for Predicting Drug-side Effect Frequency using Protein Target Information
Sungjoon Park, Sangseon Lee, Minwoo Pak, Sun Kim
IEEE Journal of Biomedical and Health Informatics  ·  01 Jan 2024  ·  doi:10.1109/JBHI.2024.3350083

2023

A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug drug interaction data and supervised contrastive learning
A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug–drug interaction data and supervised contrastive learning
Jeonghyeon Gu, Dongmin Bang, Jungseob Yi, Sangseon Lee, Dong Kyu Kim, Sun Kim
Briefings in Bioinformatics  ·  07 Aug 2023  ·  doi:10.1093/bib/bbad285
Biomedical knowledge graph learning for drug repurposing by extending guilt-by-association to multiple layers
Biomedical knowledge graph learning for drug repurposing by extending guilt-by-association to multiple layers
Dongmin Bang, Sangsoo Lim, Sangseon Lee, Sun Kim
Nature Communications  ·  15 Jun 2023  ·  doi:10.1038/s41467-023-39301-y
Improved drug response prediction by drug target data integration via network-based profiling
Improved drug response prediction by drug target data integration via network-based profiling
Minwoo Pak, Sangseon Lee, Inyoung Sung, Bonil Koo, Sun Kim
Briefings in Bioinformatics  ·  08 Feb 2023  ·  doi:10.1093/bib/bbad034
Exploring chemical space for lead identification by propagating on chemical similarity network
Exploring chemical space for lead identification by propagating on chemical similarity network
Jungseob Yi, Sangseon Lee, Sangsoo Lim, Changyun Cho, Yinhua Piao, Marie Yeo, Dongkyu Kim, Sun Kim, Sunho Lee
Computational and Structural Biotechnology Journal  ·  01 Jan 2023  ·  doi:10.1016/j.csbj.2023.08.016

2022

Multi-layer guilt-by-association-based drug repurposing by integrating clinical knowledge on biological heterogeneous networks
Multi-layer guilt-by-association-based drug repurposing by integrating clinical knowledge on biological heterogeneous networks
Dongmin Bang, Sangsoo Lim, Sangseon Lee, Sun Kim
bioRxiv  ·  24 Nov 2022  ·  doi:10.1101/2022.11.22.517225
Risk Stratification for Breast Cancer Patient by Simultaneous Learning of Molecular Subtype and Survival Outcome Using Genetic Algorithm-Based Gene Set Selection
Risk Stratification for Breast Cancer Patient by Simultaneous Learning of Molecular Subtype and Survival Outcome Using Genetic Algorithm-Based Gene Set Selection
Bonil Koo, Dohoon Lee, Sangseon Lee, Inyoung Sung, Sun Kim, Sunho Lee
Cancers  ·  25 Aug 2022  ·  doi:10.3390/cancers14174120
MLDEG: A Machine Learning Approach to Identify Differentially Expressed Genes Using Network Property and Network Propagation
MLDEG: A Machine Learning Approach to Identify Differentially Expressed Genes Using Network Property and Network Propagation
Ji Hwan Moon, Sangseon Lee, Minwoo Pak, Benjamin Hur, Sun Kim
IEEE/ACM Transactions on Computational Biology and Bioinformatics  ·  01 Jul 2022  ·  doi:10.1109/TCBB.2021.3067613
AutoCoV: tracking the early spread of COVID-19 in terms of the spatial and temporal patterns from embedding space by K-mer based deep learning
AutoCoV: tracking the early spread of COVID-19 in terms of the spatial and temporal patterns from embedding space by K-mer based deep learning
Inyoung Sung, Sangseon Lee, Minwoo Pak, Yunyol Shin, Sun Kim
BMC Bioinformatics  ·  01 Mar 2022  ·  doi:10.1186/s12859-022-04679-x
SPGP: Structure Prototype Guided Graph Pooling
SPGP: Structure Prototype Guided Graph Pooling
Sangseon Lee, Dohoon Lee, Yinhua Piao, Sun Kim
arXiv  ·  01 Jan 2022  ·  doi:10.48550/arXiv.2209.07817
On modeling and utilizing chemical compound information with deep learning technologies: A task-oriented approach
On modeling and utilizing chemical compound information with deep learning technologies: A task-oriented approach
Sangsoo Lim, Sangseon Lee, Yinhua Piao, MinGyu Choi, Dongmin Bang, Jeonghyeon Gu, Sun Kim
Computational and Structural Biotechnology Journal  ·  01 Jan 2022  ·  doi:10.1016/j.csbj.2022.07.049
Embedding of FDA Approved Drugs in Chemical Space Using Cascade Autoencoder with Metric Learning
Embedding of FDA Approved Drugs in Chemical Space Using Cascade Autoencoder with Metric Learning
Jungwoo Kim, Sangsoo Lim, Sangseon Lee, Changyun Cho, Sun Kim
2022 IEEE International Conference on Big Data and Smart Computing (BigComp)  ·  01 Jan 2022  ·  doi:10.1109/BigComp54360.2022.00080

2021

Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer
Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer
Minsu Kim, Sangseon Lee, Sangsoo Lim, Doh Young Lee, Sun Kim
Scientific Reports  ·  14 Dec 2021  ·  doi:10.1038/s41598-021-03333-5
A probabilistic model for pathway-guided gene set selection
A probabilistic model for pathway-guided gene set selection
Inyoung Kim, Sangseon Lee, Youngkuk Kim, Hugh Namkoong, Sun Kim
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)  ·  09 Dec 2021  ·  doi:10.1109/BIBM52615.2021.9669350
Construction of Condition-Specific Gene Regulatory Network Using Kernel Canonical Correlation Analysis
Construction of Condition-Specific Gene Regulatory Network Using Kernel Canonical Correlation Analysis
Dabin Jeong, Sangsoo Lim, Sangseon Lee, Minsik Oh, Changyun Cho, Hyeju Seong, Woosuk Jung, Sun Kim
Frontiers in Genetics  ·  20 May 2021  ·  doi:10.3389/fgene.2021.652623
Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space
Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space
Taeheon Lee, Sangseon Lee, Minji Kang, Sun Kim
Scientific Reports  ·  05 May 2021  ·  doi:10.1038/s41598-021-88623-8
Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands
Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands
Sangseon Lee, Taeheon Lee, Yung-Kyun Noh, Sun Kim
IEEE/ACM Transactions on Computational Biology and Bioinformatics  ·  01 May 2021  ·  doi:10.1109/TCBB.2019.2938949
DNMT1 maintains metabolic fitness of adipocytes through acting as an epigenetic safeguard of mitochondrial dynamics
DNMT1 maintains metabolic fitness of adipocytes through acting as an epigenetic safeguard of mitochondrial dynamics
Yoon Jeong Park, Sangseon Lee, Sangsoo Lim, Hahn Nahmgoong, Yul Ji, Jin Young Huh, Assim A. Alfadda, Sun Kim, Jae Bum Kim
Proceedings of the National Academy of Sciences  ·  08 Mar 2021  ·  doi:10.1073/pnas.2021073118

2020

DRIM: A Web-Based System for Investigating Drug Response at the Molecular Level by Condition-Specific Multi-Omics Data Integration
DRIM: A Web-Based System for Investigating Drug Response at the Molecular Level by Condition-Specific Multi-Omics Data Integration
Minsik Oh, Sungjoon Park, Sangseon Lee, Dohoon Lee, Sangsoo Lim, Dabin Jeong, Kyuri Jo, Inuk Jung, Sun Kim
Frontiers in Genetics  ·  12 Nov 2020  ·  doi:10.3389/fgene.2020.564792
Learning Cell-Type-Specific Gene Regulation Mechanisms by Multi-Attention Based Deep Learning With Regulatory Latent Space
Learning Cell-Type-Specific Gene Regulation Mechanisms by Multi-Attention Based Deep Learning With Regulatory Latent Space
Minji Kang, Sangseon Lee, Dohoon Lee, Sun Kim
Frontiers in Genetics  ·  30 Sep 2020  ·  doi:10.3389/fgene.2020.00869
Network Propagation for the Analysis of Multi-omics Data
Network Propagation for the Analysis of Multi-omics Data
Minwoo Pak, Dabin Jeong, Ji Hwan Moon, Hongryul Ann, Benjamin Hur, Sangseon Lee, Sun Kim
Recent Advances in Biological Network Analysis  ·  05 Sep 2020  ·  doi:10.1007/978-3-030-57173-3_9
Cancer subtype classification and modeling by pathway attention and propagation
Cancer subtype classification and modeling by pathway attention and propagation
Sangseon Lee, Sangsoo Lim, Taeheon Lee, Inyoung Sung, Sun Kim
Bioinformatics  ·  24 Mar 2020  ·  doi:10.1093/bioinformatics/btaa203

2019

Venn-diaNet : venn diagram based network propagation analysis framework for comparing multiple biological experiments
Venn-diaNet : venn diagram based network propagation analysis framework for comparing multiple biological experiments
Benjamin Hur, Dongwon Kang, Sangseon Lee, Ji Hwan Moon, Gung Lee, Sun Kim
BMC Bioinformatics  ·  01 Dec 2019  ·  doi:10.1186/s12859-019-3302-7
StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis
StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis
Dongwon Kang, Hongryul Ahn, Sangseon Lee, Chai-Jin Lee, Jihye Hur, Woosuk Jung, Sun Kim
BMC Genomics  ·  01 Dec 2019  ·  doi:10.1186/s12864-019-6283-z
SpliceHetero: An information theoretic approach for measuring spliceomic intratumor heterogeneity from bulk tumor RNA-seq
SpliceHetero: An information theoretic approach for measuring spliceomic intratumor heterogeneity from bulk tumor RNA-seq
Minsu Kim, Sangseon Lee, Sangsoo Lim, Sun Kim
PLOS ONE  ·  23 Oct 2019  ·  doi:10.1371/journal.pone.0223520
PRISM: methylation pattern-based, reference-free inference of subclonal makeup
PRISM: methylation pattern-based, reference-free inference of subclonal makeup
Dohoon Lee, Sangseon Lee, Sun Kim
Bioinformatics  ·  01 Jul 2019  ·  doi:10.1093/bioinformatics/btz327

2018

Identifying stress-related genes and predicting stress types in Arabidopsis using logical correlation layer and CMCL loss through time-series data
Identifying stress-related genes and predicting stress types in Arabidopsis using logical correlation layer and CMCL loss through time-series data
Dongwon Kang, Hongryul Ahn, Sangseon Lee, Chai-Jin Lee, Jihye Hur, Woosuk Jung, Sun Kim
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)  ·  01 Dec 2018  ·  doi:10.1109/BIBM.2018.8621581
Comprehensive and critical evaluation of individualized pathway activity measurement tools on pan-cancer data
Comprehensive and critical evaluation of individualized pathway activity measurement tools on pan-cancer data
Sangsoo Lim, Sangseon Lee, Inuk Jung, Sungmin Rhee, Sun Kim
Briefings in Bioinformatics  ·  20 Nov 2018  ·  doi:10.1093/bib/bby097
In silico experiment system for testing hypothesis on gene functions using three condition specific biological networks
In silico experiment system for testing hypothesis on gene functions using three condition specific biological networks
Chai-Jin Lee, Dongwon Kang, Sangseon Lee, Sunwon Lee, Jaewoo Kang, Sun Kim
Methods  ·  01 Aug 2018  ·  doi:10.1016/j.ymeth.2018.05.003

2017

MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data
MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data
Sangseon Lee, Youngjune Park, Sun Kim
Methods  ·  01 Jul 2017  ·  doi:10.1016/j.ymeth.2017.05.026
PINTnet: construction of condition-specific pathway interaction network by computing shortest paths on weighted PPI
PINTnet: construction of condition-specific pathway interaction network by computing shortest paths on weighted PPI
Ji Hwan Moon, Sangsoo Lim, Kyuri Jo, Sangseon Lee, Seokjun Seo, Sun Kim
BMC Systems Biology  ·  01 Mar 2017  ·  doi:10.1186/s12918-017-0387-3
Flow maximization analysis of cell cycle pathway activation status in breast cancer subtypes
Flow maximization analysis of cell cycle pathway activation status in breast cancer subtypes
Sangseon Lee, Ji Hwan Moon, Youngjune Park, Sun Kim
2017 IEEE International Conference on Big Data and Smart Computing (BigComp)  ·  01 Feb 2017  ·  doi:10.1109/BIGCOMP.2017.7881721

2016

Subtype-specific CpG island shore methylation and mutation patterns in 30 breast cancer cell lines
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 Systems Biology  ·  01 Dec 2016  ·  doi:10.1186/s12918-016-0356-2
BioVLAB-mCpG-SNP- EXPRESS : A system for multi-level and multi-perspective analysis and exploration of DNA methylation, sequence variation SNPs , and gene expression from multi-omics data
BioVLAB-mCpG-SNP- EXPRESS : A system for multi-level and multi-perspective analysis and exploration of DNA methylation, sequence variation (SNPs), and gene expression from multi-omics data
Heejoon Chae, Sangseon Lee, Seokjun Seo, Daekyoung Jung, Hyeonsook Chang, Kenneth P. Nephew, Sun Kim
Methods  ·  01 Dec 2016  ·  doi:10.1016/j.ymeth.2016.07.019
Efficiency of Methylated DNA Immunoprecipitation Bisulphite Sequencing for Whole-Genome DNA Methylation Analysis
Efficiency of Methylated DNA Immunoprecipitation Bisulphite Sequencing for Whole-Genome DNA Methylation Analysis
Hae Min Jeong, Sangseon Lee, Heejoon Chae, RyongNam Kim, Mi Jeong Kwon, Ensel Oh, Yoon-La Choi, Sun Kim, Young Kee Shin
Epigenomics  ·  08 Jun 2016  ·  doi:10.2217/epi-2016-0038