Showing results 2 to 8 of 8
Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, v.116, no.28, pp.13996 - 14001, 2019-07 |
Deep learning improves prediction of drug-drug and drug-food interactions Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, v.115, no.18, pp.E4304 - E4311, 2018-05 |
DeepRegularizer: Rapid Resolution Enhancement of Tomographic Imaging Using Deep Learning Ryu, DongHun; Ryu, Dongmin; Baek, YoonSeok; Cho, Hyungjoo; Kim, Geon; Kim, Young Seo; Lee, Yongki; et al, IEEE TRANSACTIONS ON MEDICAL IMAGING, v.40, no.5, pp.1508 - 1518, 2021-05 |
DeepTFactor: A deep learning-based tool for the prediction of transcription factors Kim, Gi Bae; Gao, Ye; Palsson, Bernhard O.; Lee, Sang Yup, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, v.118, no.2, pp.1 - 5, 2021-01 |
Fault detection and classification using artificial neural networks Heo, S.; Lee, Jay Hyung, IFAC-PapersOnLine, v.51, no.18, pp.470 - 475, 2018-01 |
Highly Oxidation-Resistant and Self-Healable MXene-Based Hydrogels for Wearable Strain Sensor Chae, Ari; Murali, G.; Lee, Seul-Yi; Gwak, Jeonghwan; Kim, Seon Joon; Jeong, Yong Jin; Kang, Hansol; et al, ADVANCED FUNCTIONAL MATERIALS, v.33, no.24, 2023-06 |
Physicochemical Profiling of Macrophage Heterogeneity Using Deep Learning Integrated Nanosensor Cytometry Han, Seunghee; Lee, Yullim; Kim, Jihan; Cho, Soo-Yeon, ACS SENSORS, v.8, no.4, pp.1676 - 1683, 2023-04 |
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