| mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation B Manavalan, S Basith, TH Shin, L Wei, G Lee Bioinformatics 35 (16), 2757-2765, 2019 | 235 | 2019 |
| MLACP: machine-learning-based prediction of anticancer peptides B Manavalan, S Basith, TH Shin, S Choi, MO Kim, G Lee Oncotarget 8 (44), 77121, 2017 | 234 | 2017 |
| Meta-4mCpred: a sequence-based meta-predictor for accurate DNA 4mC site prediction using effective feature representation B Manavalan, S Basith, TH Shin, L Wei, G Lee Molecular Therapy-Nucleic Acids 16, 733-744, 2019 | 207 | 2019 |
| AIPpred: sequence-based prediction of anti-inflammatory peptides using random forest B Manavalan, TH Shin, MO Kim, G Lee Frontiers in pharmacology 9, 276, 2018 | 195 | 2018 |
| Machine-learning-based prediction of cell-penetrating peptides and their uptake efficiency with improved accuracy B Manavalan, S Subramaniyam, TH Shin, MO Kim, G Lee Journal of proteome research 17 (8), 2715-2726, 2018 | 189 | 2018 |
| PVP-SVM: sequence-based prediction of phage virion proteins using a support vector machine B Manavalan, TH Shin, G Lee Frontiers in microbiology 9, 476, 2018 | 179 | 2018 |
| iBCE-EL: a new ensemble learning framework for improved linear B-cell epitope prediction B Manavalan, RG Govindaraj, TH Shin, MO Kim, G Lee Frontiers in immunology 9, 1695, 2018 | 175 | 2018 |
| SDM6A: a web-based integrative machine-learning framework for predicting 6mA sites in the rice genome S Basith, B Manavalan, TH Shin, G Lee Molecular Therapy-Nucleic Acids 18, 131-141, 2019 | 153 | 2019 |
| Metabolome changes in cerebral ischemia TH Shin, DY Lee, S Basith, B Manavalan, MJ Paik, I Rybinnik, ... Cells 9 (7), 1630, 2020 | 136 | 2020 |
| iGHBP: computational identification of growth hormone binding proteins from sequences using extremely randomised tree S Basith, B Manavalan, TH Shin, G Lee Computational and structural biotechnology journal 16, 412-420, 2018 | 114 | 2018 |
| PIP-EL: a new ensemble learning method for improved proinflammatory peptide predictions B Manavalan, TH Shin, MO Kim, G Lee Frontiers in immunology 9, 1783, 2018 | 108 | 2018 |
| The impact of fine particulate matter 2.5 on the cardiovascular system: a review of the invisible killer S Basith, B Manavalan, TH Shin, CB Park, WS Lee, J Kim, G Lee Nanomaterials 12 (15), 2656, 2022 | 105 | 2022 |
| AtbPpred: a robust sequence-based prediction of anti-tubercular peptides using extremely randomized trees B Manavalan, S Basith, TH Shin, L Wei, G Lee Computational and Structural Biotechnology Journal 17, 972-981, 2019 | 103 | 2019 |
| DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest B Manavalan, TH Shin, G Lee Oncotarget 9 (2), 1944, 2017 | 94 | 2017 |
| 4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N4-Methylcytosine Sites in the Mouse Genome B Manavalan, S Basith, TH Shin, DY Lee, L Wei, G Lee Cells 8 (11), 1332, 2019 | 87 | 2019 |
| Chemoresistance in the Human Triple‐Negative Breast Cancer Cell Line MDA‐MB‐231 Induced by Doxorubicin Gradient Is Associated with Epigenetic Alterations in Histone Deacetylase J Han, W Lim, D You, Y Jeong, S Kim, JE Lee, TH Shin, G Lee, S Park Journal of oncology 2019 (1), 1345026, 2019 | 76 | 2019 |
| Integration of metabolomics and transcriptomics in nanotoxicity studies TH Shin, HS Lee, HJ Park, MS Jin, MJ Paik, B Manavalan, JS Mo, G Lee BMB reports 51 (1), 14, 2018 | 73 | 2018 |
| Enhancement of the tumor penetration of monoclonal antibody by fusion of a neuropilin-targeting peptide improves the antitumor efficacy TH Shin, ES Sung, YJ Kim, KS Kim, SH Kim, SK Kim, YD Lee, YS Kim Molecular cancer therapeutics 13 (3), 651-661, 2014 | 71 | 2014 |
| Cellular internalization mechanism and intracellular trafficking of filamentous M13 phages displaying a cell-penetrating transbody and TAT peptide A Kim, TH Shin, SM Shin, CD Pham, DK Choi, MH Kwon, YS Kim PloS one 7 (12), e51813, 2012 | 71 | 2012 |
| Microfluidic assessment of mechanical cell damage by extensional stress YB Bae, HK Jang, TH Shin, G Phukan, TT Tran, G Lee, WR Hwang, ... Lab on a Chip 16 (1), 96-103, 2016 | 70 | 2016 |