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Structure-based prediction of protein- peptide binding regions using Random Forest.

, , , and . Bioinform., 34 (3): 477-484 (2018)

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Sequence-Based Prediction of Protein-Carbohydrate Binding Sites Using Support Vector Machines., , , and . Journal of Chemical Information and Modeling, 56 (10): 2123 (2016)B-factor profile prediction for RNA flexibility using support vector machines., , , , and . J. Comput. Chem., 39 (8): 407-411 (2018)SPRINT-Gly: predicting N- and O-linked glycosylation sites of human and mouse proteins by using sequence and predicted structural properties., , , , and . Bioinform., 35 (20): 4140-4146 (2019)Mal-Light: Enhancing Lysine Malonylation Sites Prediction Problem Using Evolutionary-based Features., , , , , , and . IEEE Access, (2020)Structural and energetic profiling of SARS-CoV-2 receptor binding domain antibody recognition and the impact of circulating variants., , , , , , and . PLoS Comput. Biol., (2021)Predicting lysine-malonylation sites of proteins using sequence and predicted structural features., , , , , and . J. Comput. Chem., 39 (22): 1757-1763 (2018)Structure-based prediction of protein- peptide binding regions using Random Forest., , , and . Bioinform., 34 (3): 477-484 (2018)Image Classification Using Optimized Synergetic Neural Network., and . FIRA, volume 376 of Communications in Computer and Information Science, page 170-180. Springer, (2013)SEMal: Accurate protein malonylation site predictor using structural and evolutionary information., , , , , and . Comput. Biol. Medicine, (2020)SPPPred: Sequence-Based Protein-Peptide Binding Residue Prediction Using Genetic Programming and Ensemble Learning., , and . IEEE ACM Trans. Comput. Biol. Bioinform., 20 (3): 2029-2040 (2023)