ArticleBioMed research international
ProFold: Protein Fold Classification with Additional Structural Features and a Novel Ensemble Classifier.
Article in BioMed research international. 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.
- DeepProtein: deep learning library and benchmark for protein sequence learning.Bioinformatics (Oxford, England) · 2025Article
- PETA: evaluating the impact of protein transfer learning with sub-word tokenization on downstream applications.Journal of cheminformatics · 2024Article
- BioS2Net: Holistic Structural and Sequential Analysis of Biomolecules Using a Deep Neural Network.International journal of molecular sciences · 2022Article
- DeepFrag-k: a fragment-based deep learning approach for protein fold recognition.BMC bioinformatics · 2020Article
- Recent Progress in Machine Learning-Based Methods for Protein Fold Recognition.International journal of molecular sciences · 2016Review
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Authors and funding
4 authors.
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Abstract
Protein fold classification plays an important role in both protein functional analysis and drug design. The number of proteins in PDB is very large, but only a very small part is categorized and stored in the SCOPe database. Therefore, it is necessary to develop an efficient method for protein fold classification. In recent years, a variety of classification methods have been used in many protein fold classification studies. In this study, we propose a novel classification method called proFold. We import protein tertiary structure in the period of feature extraction and employ a novel ensemble strategy in the period of classifier training. Compared with existing similar ensemble classifiers using the same widely used dataset (DD-dataset), proFold achieves 76.2% overall accuracy. Another two commonly used datasets, EDD-dataset and TG-dataset, are also tested, of which the accuracies are 93.2% and 94.3%, higher than the existing methods. ProFold is available to the public as a web-server.
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