Development of an Electroporation System for Preclinical Use. - Jeong Han Yi; Hyung Sik Kim; Hong Bae Kim; Saeyoung Ahn; Youn-Suk Choi (BMEI (2), 2008)

Efficient learning of non-autoregressive graph variational autoencoders for molecular graph generation. - Youngchun Kwon; Jiho Yoo; Youn-Suk Choi; Wonjoon Song; Dongseon Lee; Seokho Kang 001 (J. Cheminformatics, 2019)

Compressed graph representation for scalable molecular graph generation. - Youngchun Kwon; Dongseon Lee; Youn-Suk Choi; Kyoham Shin; Seokho Kang 001 (J. Cheminformatics, 2020)

Predictive Modeling of NMR Chemical Shifts without Using Atomic-Level Annotations. - Seokho Kang 001; Youngchun Kwon; Dongseon Lee; Youn-Suk Choi (J. Chem. Inf. Model., 2020)

Neural Message Passing for NMR Chemical Shift Prediction. - Youngchun Kwon; Dongseon Lee; Youn-Suk Choi; Myeonginn Kang; Seokho Kang 001 (J. Chem. Inf. Model., 2020)

Valid, Plausible, and Diverse Retrosynthesis Using Tied Two-Way Transformers with Latent Variables. - Eunji Kim 001; Dongseon Lee; Youngchun Kwon; Min Sik Park; Youn-Suk Choi (J. Chem. Inf. Model., 2021)

Uncertainty-aware prediction of chemical reaction yields with graph neural networks. - Youngchun Kwon; Dongseon Lee; Youn-Suk Choi; Seokho Kang 001 (J. Cheminformatics, 2022)

Generative Modeling to Predict Multiple Suitable Conditions for Chemical Reactions. - Youngchun Kwon; Sun Kim; Youn-Suk Choi; Seokho Kang 001 (J. Chem. Inf. Model., 2022)

Automated Solubility Analysis System and Method Using Computer Vision and Machine Learning. - Gahee Kim; Minwoo Jeon; Hyun Do Choi; Jun Ki Cho; Youn-Suk Choi; Hyoseok Hwang (CoRR, 2023)

Improving chemical reaction yield prediction using pre-trained graph neural networks. - Jongmin Han; Youngchun Kwon; Youn-Suk Choi; Seokho Kang 001 (J. Cheminformatics, 2024)

Enhancing chemical reaction search through contrastive representation learning and human-in-the-loop. - Youngchun Kwon; Hyunjeong Jeon; Joonhyuk Choi; Youn-Suk Choi; Seokho Kang 001 (J. Cheminformatics, 2025)