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Publications

NSF MRI

Acknowledgement: We acknowledge NSF MRI (#2117941) for GPU Cluster support.

2026

  1. [J] Beomsu Baek, Eunyoung Jang, Sai Phani Parsa, Youngsoon Kim*, and Mingon Kang*, “Knowledge-guided learning with curated prior genetic biomarkers for robust model interpretation“, Bioinformatics, 42(Supplement_2), btag411, 2026
  2. [C] Eunyoung Jang, Euiseong Ko, and Mingon Kang*, “Inference of disease-associated pathway interaction networks using graph neural networks“, Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, ACM BCB, 2026
  3. [C] Suhyeong Jeon, Louis Dumontet, So-Ra Han, Tae-jin Oh, and Mingon Kang*, “IDF-EC: Interpretable dynamic feature-logit fusion for enzyme commission number prediction“, Proceedings of the 17th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, ACM BCB, 2026
  4. [J] Euiseong Ko, Sai Phani Parsa, Sai Chandra Kosaraju, Tesfaye B. Mersha*, and Mingon Kang*, “Fairness-aware supervised hierarchical contrastive semantic learning for sexual dimorphism analysis“, Bioinformatics, 42(Supplement_1), btag237, 2026
  5. [C] Daniel Ogenrwot and John Businge*, “AgenticFlict: A large-scale dataset of merge conflicts in AI coding agent pull requests on GitHub“, Proceedings of the 3rd ACM International Conference on AI-Powered Software, ACM Alware, 2026
  6. [J] Woo-Haeng Lee, Louis Dumontet, KyungMin Jung, Hyun Lee, Gobinda Thapa, Tae-Jin Oh*, and Mingon Kang*, “Interpretable convolutional neural networks for sequence-based classification and discovery of plastic-degrading enzymes“, Applied and Environmental Microbiology, 92(5), e01586-25, 2026
  7. [C] Daniel Ogenrwot and John Businge*, “How AI coding agents modify code: A large-scale study of GitHub pull requests“, Proceedings of the 23rd International Conference on Mining Software Repositories, ACM MSR, 2026
  8. [J] Ki-Hwa Kim, Avinash Yaganapu, Sai Kosaraju, Ashish Bhatt, Yun Lyna Luo, Sai Phani Parsa, Juyeon Park, Hyun Lee, Jun Hyuck Lee, Tae-Jin Oh*, and Mingon Kang*, “Prediction of bacterial protein-compound interactions with only positive samples“, Bioinformatics, 42(3), btag067, 2026
  9. [J] Louis Dumontet, So-Ra Han, Jun Hyuck Lee, Tae-Jin Oh*, and Mingon Kang*, “Trustworthy prediction of enzyme commission numbers using a hierarchical interpretable transformer“, Nature Communications, 17, 1146, 2026
  10. [J] Louis Dumontet, So-Ra Han, Axel Prouvost, Jun Hyuck Lee, Tae-Jin Oh*, and Mingon Kang*, “Interpretable Kolmogorov-Arnold networks for enzyme commission number prediction“, npj Artificial Intelligence, 2, 11, 2026
  11. [J] Beomsu Baek, Jongkwon Jo, Mingon Kang*, and Youngsoon Kim*, “Stochastic LASSO for extremely high-dimensional genomic data“, Scientific Reports, 16, 5250, 2026

2025

  1. [J] Sai Chandra Kosaraju, Sai Phani Parse, Dae Hyun Song, Hyo Jung An, Yoon-La Choi, Joungho Han, Jung Wook Yang*, and Mingon Kang*, “Evidential deep learning-based ALK-expression screening using H&E-stained histopathological images“, npj Digital Medicine, 8(1), 610, 2025
  2. [J] Raja Mallina and Bryar Shareef*, “XBusNet: Text-guided breast ultrasound segmentation via multimodal vision-language learning“, Diagnostics, 15(22), 2849, 2025
  3. [C] Hasan Serdar Arikan, Rakibul Hassan, Shubhashish Kar, Doru Thom Popovici, and Shaikh Arifuzzaman*, “GCN-driven CUDA parameter optimization for parallel triangle counting in graphs“, 2025 IEEE High Performance Extreme Computing Conference, IEEE, 2025
  4. [J] Cristian Arteaga and JeeWoong Park*, “A large language model framework to uncover underreporting in traffic crashes“, Journal of Safety Research, 92, 1-13, 2025

2024

  1. [J] So-Ra Han, Mingyu Park, Sai Kosaraju, JeungMin Lee, Hyun Lee, Jun Hyuck Lee, Tae-Jin Oh*, and Mingon Kang*, “Evidential deep learning for trustworthy prediction of enzyme commission number“, Briefings in Bioinformatics, 25(1), bbad401, 2024
  2. [J] Avinash Yaganapu and Mingon Kang*, “Multi-layered self-attention mechanism for weakly supervised semantic segmentation“, Computer Vision and Image Understanding, 239, 2024
  3. [J] Euiseong Ko, Youngsoon Kim, Farhad Shokoohi, Tesfaye B. Mersha*, and Mingon Kang*, “SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis“, Briefings in Bioinformatics, 25(4), bbae239, 2024