| 2018 | | Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy | Balachandran, Manavalan, 신태환, 이광 |
| 2019 | | mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides | Balachandran, Manavalan, 이광 |
| 2019 | | mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2019 | | Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2017 | | MLACP: machine-learning-based prediction of anticancer peptides | Balachandran, Manavalan, 이광 |
| 2018 | | PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions | Balachandran, Manavalan, 이광 |
| 2019 | | Prediction of S-nitrosylation sites by integrating support vector machines and random forest | Balachandran, Manavalan |
| 2018 | | PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine | Balachandran, Manavalan, 이광 |
| 2019 | | SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2019 | | Silica-coated magnetic nanoparticles induce glucose metabolic dysfunction in vitro via the generation of reactive oxygen species | Balachandran, Manavalan, Basith, Shaherin, 박찬배, 신태환, 이광 |
