| 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 | 85 | 2020 |
| 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 | 82 | 2021 |
| 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 | 66 | 2021 |
| Molecular subtype classification of low‐grade gliomas using magnetic resonance imaging‐based radiomics and machine learning LHT Lam, DT Do, DTN Diep, DLN Nguyet, QD Truong, TT Tri, HN Thanh, ... NMR in Biomedicine 35 (11), e4792, 2022 | 55 | 2022 |
| Using extreme gradient boosting to identify origin of replication in Saccharomyces cerevisiae via hybrid features NQKL Duyen Thi Do Genomics 112 (3), 2020 | 54 | 2020 |
| A computational framework based on ensemble deep neural networks for essential genes identification NQK Le, DT Do, TNK Hung, LHT Lam, TT Huynh, NTK Nguyen International journal of molecular sciences 21 (23), 9070, 2020 | 52 | 2020 |
| A sequence-based prediction of Kruppel-like factors proteins using XGBoost and optimized features NQK Le, DT Do, QA Le Gene 787, 145643, 2021 | 39 | 2021 |
| Identification of gene expression signatures for psoriasis classification using machine learning techniques NQK Le, DT Do, NTK Nguyen, TNK Hung, NTT Trang Medicine in Omics 1, 100001, 2021 | 20 | 2021 |
| Improving MGMT methylation status prediction of glioblastoma through optimizing radiomics features using genetic algorithm-based machine learning approach DT Do, MR Yang, LHT Lam, NQK Le, YW Wu Scientific Reports 12 (1), 13412, 2022 | 18 | 2022 |
| A sequence-based approach for identifying recombination spots in Saccharomyces cerevisiae by using hyper-parameter optimization in FastText and support vector machine DT Do, NQK Le Chemometrics and Intelligent Laboratory Systems 194, 103855, 2019 | 13 | 2019 |
| A radiomics-based machine learning model for prediction of tumor mutational burden in lower-grade gliomas LHT Lam, NT Chu, TO Tran, DT Do, NQK Le Cancers 14 (14), 3492, 2022 | 12 | 2022 |
| Novel regulations of MEF2-A, MEF2-D, and CACNA1S in the functional incompetence of adipose-derived mesenchymal stem cells by induced indoxyl sulfate in chronic kidney disease D Thi Do, NN Phan, CY Wang, Z Sun, YC Lin Cytotechnology 68, 2589-2604, 2016 | 8 | 2016 |
| Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains DT Do, MR Yang, TNS Vo, NQK Le, YW Wu Computational and Structural Biotechnology Journal, 2024 | | 2024 |
| Inhibition of Src kinase activity reduces heart rate with slight alteration of heart rate variability JH Jiang, J Ho, NN Phan, DT Tian, TD Do, H Chang, YC Lin The FASEB Journal 27, 706.1-706.1, 2013 | | 2013 |
| Molecular subtypes classification of low-grade gliomas patients using MRI-based radiomics and machine learning LHT Lam, DT Do, DTN Diep, DLN Nguyet, QD Truong, TT Tri, HN Thanh, ... | | |
