Identification of temporal association rules from time-series microarray data set: temporal association rules. - Hojung Nam; Ki Young Lee; Doheon Lee (DTMBIO, 2008)

Combining tissue transcriptomics and urine metabolomics for breast cancer biomarker identification. - Hojung Nam; Bong Chul Chung; Younghoon Kim; Ki Young Lee; Doheon Lee (Bioinform., 2009)

Identification of temporal association rules from time-series microarray data sets. - Hojung Nam; Ki Young Lee; Doheon Lee (BMC Bioinform., 2009)

Exploring molecular links between lymph node invasion and cancer prognosis in human breast cancer. - Sangwoo Kim; Hojung Nam; Doheon Lee (BMC Syst. Biol., 2011)

Integrative Database for Exploring Compound Combinations of Natural Products for Medical Effects. - Suhyun Ha; Sunyong Yoo; Moonshik Shin; Jin Sook Kwak; Oran Kwon; Min Chang Choi; Keon Wook Kang; Hojung Nam; Doheon Lee (DTMBIO@CIKM, 2014)

Identification of a Specific Base Sequence of Pathogenic E. Coli through a Genomic Analysis. - Soobok Joe; Hojung Nam (DTMBIO@CIKM, 2014)

Identification of Genomic Features in the Classification of Loss- and Gain-of-Function Mutation: [Extended Abstract]. - Seunghwan Jung; Sejoon Lee; Sangwoo Kim; Hojung Nam (DTMBIO@CIKM, 2014)

A Systems Approach to Predict Oncometabolites via Context-Specific Genome-Scale Metabolic Networks. - Hojung Nam; Miguel Campodonico; Aarash Bordbar; Daniel R. Hyduke; Sangwoo Kim; Daniel C. Zielinski; Bernhard O. Palsson (PLoS Comput. Biol., 2014)

Prediction of Compound-Target Interactions of Natural Products Using Large-scale Drug and Protein Information. - Jongsoo Keum; Sunyong Yoo; Hojung Nam (DTMBIO@CIKM, 2015)

Toxicity Predictions using Compound Descriptions. - Eunyoung Kim; Sangwoo Kim; Suhyun Ha; Hojung Nam (DTMBIO@CIKM, 2015)

SoloDel: a probabilistic model for detecting low-frequent somatic deletions from unmatched sequencing data. - Junho Kim; Sanghyeon Kim; Hojung Nam; Sangwoo Kim; Doheon Lee (Bioinform., 2015)

Identification of genomic features in the classification of loss- and gain-of-function mutation. - Seunghwan Jung; Sejoon Lee; Sangwoo Kim; Hojung Nam (BMC Medical Informatics Decis. Mak., 2015)

Prediction of compound-target interactions of natural products using large-scale drug and protein information. - Jongsoo Keum; Sunyong Yoo; Doheon Lee; Hojung Nam (BMC Bioinform., 2016)

Prognostic factor analysis for breast cancer using gene expression profiles. - Soobok Joe; Hojung Nam (BMC Medical Informatics Decis. Mak., 2016)

In Silico Simulation of Signal Cascades in Biomedical Networks Based on the Production Rule System. - Sangwoo Kim; Hojung Nam (ISBRA, 2017)

Prediction models for drug-induced hepatotoxicity by using weighted molecular fingerprints. - Eunyoung Kim; Hojung Nam (BMC Bioinform., 2017)

A Data-Driven Approach for Identifying Medicinal Combinations of Natural Products. - Sunyong Yoo; Suhyun Ha; Moonshik Shin; Kyungrin Noh; Hojung Nam; Doheon Lee (IEEE Access, 2018)

Identification of drug-target interaction by a random walk with restart method on an interactome network. - Ingoo Lee; Hojung Nam (BMC Bioinform., 2018)

Predicting the Absorption Potential of Chemical Compounds Through a Deep Learning Approach. - Moonshik Shin; Donjin Jang; Hojung Nam; Kwang Hyung Lee; Doheon Lee (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Drug repositioning of herbal compounds via a machine-learning approach. - Eunyoung Kim; A.-Sol Choi; Hojung Nam (BMC Bioinform., 2019)

DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences. - Ingoo Lee; Jongsoo Keum; Hojung Nam (PLoS Comput. Biol., 2019)

DTMBIO 2020: The Fourteenth International Workshop on Data and Text Mining in Biomedical Informatics. - Hyojung Paik; Sunyong Yoo; Hojung Nam; Mark Stevenson; Albert No (CIKM, 2020)

Prediction model construction of mouse stem cell pluripotency using CpG and non-CpG DNA methylation markers. - Soobok Joe; Hojung Nam (BMC Bioinform., 2020)

hERG-Att: Self-attention-based deep neural network for predicting hERG blockers. - Hyunho Kim; Hojung Nam (Comput. Biol. Chem., 2020)

HiDRA: Hierarchical Network for Drug Response Prediction with Attention. - Iljung Jin; Hojung Nam (J. Chem. Inf. Model., 2021)

BayeshERG: a robust, reliable and interpretable deep learning model for predicting hERG channel blockers. - Hyunho Kim; Minsu Park; Ingoo Lee; Hojung Nam (Briefings Bioinform., 2022)

Infusing Linguistic Knowledge of SMILES into Chemical Language Models. - Ingoo Lee; Hojung Nam (CoRR, 2022)

DeSIDE-DDI: interpretable prediction of drug-drug interactions using drug-induced gene expressions. - Eunyoung Kim; Hojung Nam (J. Cheminformatics, 2022)

Sequence-based prediction of protein binding regions and drug-target interactions. - Ingoo Lee; Hojung Nam (J. Cheminformatics, 2022)

LOGICS: Learning optimal generative distribution for designing de novo chemical structures. - Bongsung Bae; Haelee Bae; Hojung Nam (J. Cheminformatics, 2023)

DD-PRiSM: a deep learning framework for decomposition and prediction of synergistic drug combinations. - Iljung Jin; Songyeon Lee; Martin Schmuhalek; Hojung Nam (Briefings Bioinform., 2024)

AI-guided discovery and optimization of antimicrobial peptides through species-aware language model. - Daehun Bae; Minsang Kim; Jiwon Seo; Hojung Nam (Briefings Bioinform., 2025)