Protein folds prediction is an essential and basic problem for protein structure and function
research. As far as we see, there are generally three problems for the protein folds prediction. The first
one is the overfitting problem due to the lack of training samples. The second one is the missing information
of hierarchical labels. Small size of the current benchmark is another troubling issue. In this
paper, we proposed structured SVM to overcome the first and second problems. We also contributed
three comparatively huge datasets as benchmark for protein folds prediction. Experiments on different datasets can prove
the performance and robustness of our structured SVM.
Keywords: Structured support vector machine, protein folds prediction, protein structure, machine learning, bioinformatics,
protein secondary structure.
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