ArticleMolecules (Basel, Switzerland)2020
A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers.
Article in Molecules (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Prediction of the Trimer Protein Interface Residue Pair by CNN-GRU Model Based on Multi-Feature Map.Nanomaterials (Basel, Switzerland) · 2025Article
- AdaBoost model for rockburst intensity prediction considering class differences and quantitative characterization of misclassification difference.Scientific reports · 2024Article
- Review and Comparative Analysis of Methods and Advancements in Predicting Protein Complex Structure.Interdisciplinary sciences, computational life sciences · 2024Review
- Prediction of the tetramer protein complex interaction based on CNN and SVM.Frontiers in genetics · 2023Article
- Protein-protein interaction and non-interaction predictions using gene sequence natural vector.Communications biology · 2022Article
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Authors and funding
2 authors.
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Abstract
Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein-protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and geometric properties of amino acids and the influence of surrounding amino acids. Different descriptors and different combinations may give different prediction results. We propose feature combination engineering based on correlation coefficients and F-values. The accuracy of our method is 65.38% in independent test set, indicating biological significance. Our predictions are consistent with the experimental results. It shows the effectiveness and reliability of our method to predict interface residue pairs of protein trimers.
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