Tae-Jin Oh

According to our database, Tae-Jin Oh authored at least 6 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Deep learning for precipitation nowcasting: A survey from the perspective of time series forecasting.

Sojung An, Tae-Jin Oh, Eunha Sohn, Donghyun Kim

Expert Syst. Appl., 2025

2023

ResBiGAAT: Residual Bi-GRU with attention for protein-ligand binding affinity prediction.

Gelany Aly Abdelkader, Soualihou Ngnamsie Njimbouom, Tae-Jin Oh, Jeong-Dong Kim

Comput. Biol. Chem., December, 2023

Evidential deep learning for trustworthy prediction of enzyme commission number.

So-Ra Han, Mingyu Park, Sai Kosaraju, Jeungmin Lee, Hyun Lee, Jun Hyuck Lee, Tae-Jin Oh, Mingon Kang

Briefings Bioinform., November, 2023

Efficient Machine Learning-Based Prediction of CYP450 Inhibition.

Gelany Aly Abdelkader, Soualihou Ngnamsie Njimbouom, Prince Delator Gidiglo, Tae-Jin Oh, Jeong-Dong Kim

Proceedings of the Database and Expert Systems Applications, 2023

2022

Divergence/Connection Preservation Scheme in the Curvilinear Domain with a Small Geometric Approximation Error.

Sehun Chun, Tae-Jin Oh

J. Sci. Comput., 2022

2021

GCRNN: graph convolutional recurrent neural network for compound-protein interaction prediction.

Ermal Elbasani, Soualihou Ngnamsie Njimbouom, Tae-Jin Oh, Eung-Hee Kim, Hyun Lee, Jeong-Dong Kim

BMC Bioinform., 2021