| 2019 | | 4mCpred-EL: An Ensemble Learning Framework for Identification of DNA N(4)-methylcytosine Sites in the Mouse Genome | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2022 | | Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2 | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2021 | | Computational prediction of species-specific yeast DNA replication origin via iterative feature representation | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2021 | | Critical evaluation of web-based DNA N6-methyladenine site prediction tools | Balachandran, Manavalan |
| 2022 | | Development of Anticancer Peptides Using Artificial Intelligence and Combinational Therapy for Cancer Therapeutics | 신태환, 이광 |
| 2018 | | DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest | Balachandran, Manavalan, 이광 |
| 2020 | | Empirical Comparison and Analysis of Web-Based DNA N (4)-Methylcytosine Site Prediction Tools | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2020 | | Evolution of Machine Learning Algorithms in the Prediction and Design of Anticancer Peptides | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광, 이다연 |
| 2021 | | Integrative machine learning framework for the identification of cell-specific enhancers from the human genome | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2020 | | Machine intelligence in peptide therapeutics: A next-generation tool for rapid disease screening | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2018 | | Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy | Balachandran, Manavalan, 신태환, 이광 |
| 2021 | | NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning | Balachandran, Manavalan |
| 2018 | | PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions | Balachandran, Manavalan, 이광 |
| 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 |
| 2021 | | StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides | Balachandran, Manavalan |
| 2022 | | STALLION: A stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2022 | | THRONE: A New Approach for Accurate Prediction of Human RNA N7-Methylguanosine Sites | Basith, Shaherin, 이광 |
