| 2022 | | Accelerating bioactive peptide discovery via mutual information-based meta-learning | Balachandran, Manavalan |
| 2022 | | SCMTHP: A New Approach for Identifying and Characterizing of Tumor-Homing Peptides Using Estimated Propensity Scores of Amino Acids | Balachandran, Manavalan |
| 2022 | | Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2 | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2022 | | STALLION: A stacking-based ensemble learning framework for prokaryotic lysine acetylation site prediction | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2021 | | SortPred: The first machine learning based predictor to identify bacterial sortases and their classes using sequence-derived information | Balachandran, Manavalan |
| 2021 | | Mapping the intramolecular communications among different glutamate dehydrogenase states using molecular dynamics | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2021 | | Silica-coated magnetic nanoparticles activate microglia and induce neurotoxic d-serine secretion | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2021 | | Silica-coated magnetic-nanoparticle-induced cytotoxicity is reduced in microglia by glutathione and citrate identified using integrated omics | Balachandran, Manavalan, Basith, Shaherin, 강엽, 김아영, 백은주, 신태환, 이광 |
| 2021 | | Decrease in membrane fluidity and traction force induced by silica-coated magnetic nanoparticles | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광, 이다연 |
| 2021 | | Umpred-frl: A new approach for accurate prediction of umami peptides using feature representation learning | Balachandran, Manavalan |
| 2021 | | BERT4Bitter: A bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides | Balachandran, Manavalan |
| 2021 | | Integrative machine learning framework for the identification of cell-specific enhancers from the human genome | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2021 | | NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning | Balachandran, Manavalan |
| 2021 | | StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides | Balachandran, Manavalan |
| 2021 | | Critical evaluation of web-based DNA N6-methyladenine site prediction tools | Balachandran, Manavalan |
| 2021 | | Computational prediction of species-specific yeast DNA replication origin via iterative feature representation | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2021 | | Computational prediction and interpretation of cell-specific replication origin sites from multiple eukaryotes by exploiting stacking framework | Balachandran, Manavalan |
| 2021 | | Meta-i6mA: An interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2020 | | Extremely-randomized-tree-based Prediction of N(6)-Methyladenosine Sites in Saccharomyces cerevisiae | Balachandran, Manavalan |
| 2020 | | Metabolome Changes in Cerebral Ischemia | Balachandran, Manavalan, Basith, Shaherin, 신태환, 안정환, 이광 |
| 2020 | | Evolution of Machine Learning Algorithms in the Prediction and Design of Anticancer Peptides | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광, 이다연 |
| 2020 | | HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation | Balachandran, Manavalan, Basith, Shaherin, 이광 |
| 2020 | | Empirical comparison and analysis of web-based cell-penetrating peptide prediction tools | Balachandran, Manavalan |
| 2020 | | Empirical Comparison and Analysis of Web-Based DNA N (4)-Methylcytosine Site Prediction Tools | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2020 | | i4mC-Mouse: Improved identification of DNA N4-methylcytosine sites in the mouse genome using multiple encoding schemes | Balachandran, Manavalan |
| 2020 | | i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome | Balachandran, Manavalan |
| 2020 | | Machine intelligence in peptide therapeutics: A next-generation tool for rapid disease screening | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2020 | | i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation | Balachandran, Manavalan |
| 2019 | | Silica-Coated Magnetic Nanoparticles Decrease Human Bone Marrow-Derived Mesenchymal Stem Cell Migratory Activity by Reducing Membrane Fluidity and Impairing Focal Adhesion | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 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 |
| 2019 | | Prediction of S-nitrosylation sites by integrating support vector machines and random forest | Balachandran, Manavalan |
| 2019 | | SDM6A: A Web-Based Integrative Machine-Learning Framework for Predicting 6mA Sites in the Rice Genome | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2019 | | AtbPpred: A Robust Sequence-Based Prediction of Anti-Tubercular Peptides Using Extremely Randomized Trees | 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 |
| 2019 | | Iterative feature representations improve N4-methylcytosine site prediction | Balachandran, Manavalan |
| 2019 | | mACPpred: A Support Vector Machine-Based Meta-Predictor for Identification of Anticancer Peptides | Balachandran, Manavalan, 이광 |
| 2019 | | A Molecular Dynamics Approach to Explore the Intramolecular Signal Transduction of PPAR-alpha | 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 |
| 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 |
| 2018 | | Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy | Balachandran, Manavalan, 신태환, 이광 |
| 2018 | | iGHBP: Computational identification of growth hormone binding proteins from sequences using extremely randomised tree | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광 |
| 2018 | | Bidirectional Transcriptome Analysis of Rat Bone Marrow-Derived Mesenchymal Stem Cells and Activated Microglia in an In Vitro Coculture System | Balachandran, Manavalan, 이광 |
| 2018 | | PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions | Balachandran, Manavalan, 이광 |
| 2018 | | iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction | Balachandran, Manavalan, 이광 |
| 2018 | | AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest | Balachandran, Manavalan, 이광 |
| 2018 | | PVP-SVM: Sequence-Based Prediction of Phage Virion Proteins Using a Support Vector Machine | Balachandran, Manavalan, 이광 |
| 2018 | | Integration of metabolomics and transcriptomics in nanotoxicity studies | Balachandran, Manavalan, 모정순, 이광 |
| 2018 | | DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest | Balachandran, Manavalan, 이광 |
| 2017 | | MLACP: machine-learning-based prediction of anticancer peptides | Balachandran, Manavalan, 이광 |
