2022 | | Accelerating bioactive peptide discovery via mutual information-based meta-learning | Balachandran, Manavalan |
2022 | | Comparative analysis of machine learning-based approaches for identifying therapeutic peptides targeting SARS-CoV-2 | Balachandran, Manavalan, Basith, Shaherin, 이광 |
2020 | | Evolution of Machine Learning Algorithms in the Prediction and Design of Anticancer Peptides | Balachandran, Manavalan, Basith, Shaherin, 신태환, 이광, 이다연 |
2013 | | Exendin-4 inhibits glucolipotoxic ER stress in pancreatic β cells via regulation of SREBP1c and C/EBPβ transcription factors. | 강엽 |
2020 | | HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation | Balachandran, Manavalan, Basith, Shaherin, 이광 |
2011 | | Involvement of visfatin in palmitate-induced upregulation of inflammatory cytokines in hepatocytes. | 강엽, 김대중, 김혜진, 이관우, 최용준, 한승진 |
2020 | | Machine intelligence in peptide therapeutics: A next-generation tool for rapid disease screening | Balachandran, Manavalan, Basith, Shaherin, 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 |
2010 | | Molecular modeling of the reductase domain to elucidate the reaction mechanism of reduction of peptidyl thioester into its corresponding alcohol in non-ribosomal peptide synthetases. | 이광 |
2021 | | Molecular perspectives of SARS-CoV-2: Pathology, immune evasion, and therapeutic interventions | SHAH, MASAUD, 우현구 |
2021 | | StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides | Balachandran, Manavalan |
2021 | | Umpred-frl: A new approach for accurate prediction of umami peptides using feature representation learning | Balachandran, Manavalan |