| A transformer architecture based on BERT and 2D convolutional neural network to identify DNA enhancers from sequence information NQK Le, QT Ho, TTD Nguyen, YY Ou Briefings in bioinformatics 22 (5), bbab005, 2021 | 131 | 2021 |
| iEnhancer-5Step: identifying enhancers using hidden information of DNA sequences via Chou's 5-step rule and word embedding NQK Le, EKY Yapp, QT Ho, N Nagasundaram, YY Ou, HY Yeh Analytical biochemistry 571, 53-61, 2019 | 131 | 2019 |
| Machine learning-based radiomics signatures for EGFR and KRAS mutations prediction in non-small-cell lung cancer NQK Le, QH Kha, VH Nguyen, YC Chen, SJ Cheng, CY Chen International journal of molecular sciences 22 (17), 9254, 2021 | 97 | 2021 |
| Classifying promoters by interpreting the hidden information of DNA sequences via deep learning and combination of continuous fasttext N-grams NQK Le, EKY Yapp, N Nagasundaram, HY Yeh Frontiers in bioengineering and biotechnology 7, 305, 2019 | 97 | 2019 |
| XGBoost improves classification of MGMT promoter methylation status in IDH1 wildtype glioblastoma NQK Le, DT Do, FY Chiu, EKY Yapp, HY Yeh, CY Chen Journal of personalized medicine 10 (3), 128, 2020 | 92 | 2020 |
| Incorporating deep learning with convolutional neural networks and position specific scoring matrices for identifying electron transport proteins NQK Le, QT Ho, YY Ou Journal of Computational Chemistry 38 (23), 2000-2006, 2017 | 91 | 2017 |
| On the road to explainable AI in drug-drug interactions prediction: A systematic review TH Vo, NTK Nguyen, QH Kha, NQK Le Computational and Structural Biotechnology Journal 20, 2112-2123, 2022 | 88 | 2022 |
| Radiomics-based machine learning model for efficiently classifying transcriptome subtypes in glioblastoma patients from MRI NQK Le, TNK Hung, DT Do, LHT Lam, LH Dang, TT Huynh Computers in Biology and Medicine 132, 104320, 2021 | 88 | 2021 |
| Deep transformers and convolutional neural network in identifying DNA N6-methyladenine sites in cross-species genomes NQK Le, QT Ho Methods 204, 199-206, 2022 | 76 | 2022 |
| Identification of clathrin proteins by incorporating hyperparameter optimization in deep learning and PSSM profiles NQK Le, TT Huynh, EKY Yapp, HY Yeh Computer methods and programs in biomedicine 177, 81-88, 2019 | 75 | 2019 |
| Application of Computational Biology and Artificial Intelligence Technologies in Cancer Precision Drug Discovery N Nagarajan, EKY Yapp, NQK Le, B Kamaraj, AM Al-Subaie, HY Yeh BioMed research international 2019, 2019 | 73 | 2019 |
| An ai‐based prediction model for drug‐drug interactions in osteoporosis and Paget's diseases from smiles TNK Hung, NQK Le, NH Le, L Van Tuan, TP Nguyen, C Thi, JH Kang Molecular informatics 41 (6), 2100264, 2022 | 71 | 2022 |
| Using deep neural networks and biological subwords to detect protein S-sulfenylation sites DT Do, TQT Le, NQK Le Briefings in Bioinformatics 22 (3), bbaa128, 2021 | 67 | 2021 |
| BERT-Promoter: An improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection NQK Le, QT Ho, VN Nguyen, JS Chang Computational Biology and Chemistry 99, 107732, 2022 | 66 | 2022 |
| iEnhancer-ECNN: identifying enhancers and their strength using ensembles of convolutional neural networks QH Nguyen, TH Nguyen-Vo, NQK Le, TTT Do, S Rahardja, BP Nguyen BMC genomics 20, 1-10, 2019 | 65 | 2019 |
| Prediction of anticancer peptides based on an ensemble model of deep learning and machine learning using ordinal positional encoding Q Yuan, K Chen, Y Yu, NQK Le, MCH Chua Briefings in Bioinformatics 24 (1), bbac630, 2023 | 64 | 2023 |
| iMotor-CNN: Identifying molecular functions of cytoskeleton motor proteins using 2D convolutional neural network via Chou's 5-step rule NQK Le, EKY Yapp, YY Ou, HY Yeh Analytical biochemistry 575, 17-26, 2019 | 64 | 2019 |
| iN6-methylat (5-step): identifying DNA N6-methyladenine sites in rice genome using continuous bag of nucleobases via Chou’s 5-step rule NQK Le Molecular Genetics and Genomics 294 (5), 1173-1182, 2019 | 63 | 2019 |
| Classifying the molecular functions of Rab GTPases in membrane trafficking using deep convolutional neural networks NQK Le, QT Ho, YY Ou Analytical biochemistry 555, 33-41, 2018 | 63 | 2018 |
| Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs NQK Le, YY Ou BMC Bioinformatics 17 (1), 298, 2016 | 62 | 2016 |
Yu-Yen OuProfessor, Department of Computer Science and Engineering, Yuan-Ze University在 saturn.yzu.edu.tw 的电子邮件经过验证
