ArticleTheScientificWorldJournal2014
Protein binding site prediction by combining hidden Markov support vector machine and profile-based propensities.
Article in TheScientificWorldJournal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Automatic generation of bioinformatics tools for predicting protein-ligand binding sites.Bioinformatics (Oxford, England) · 2016Article
- iMiRNA-SSF: Improving the Identification of MicroRNA Precursors by Combining Negative Sets with Different Distributions.Scientific reports · 2016Article
- Progress and challenges in predicting protein interfaces.Briefings in bioinformatics · 2016Review
- Protein Remote Homology Detection Based on an Ensemble Learning Approach.BioMed research international · 2016Article
- Protein remote homology detection by combining Chou's distance-pair pseudo amino acid composition and principal component analysis.Molecular genetics and genomics : MGG · 2015Article
- Survey of Natural Language Processing Techniques in Bioinformatics.Computational and mathematical methods in medicine · 2015Review
- Development of a machine learning method to predict membrane protein-ligand binding residues using basic sequence information.Advances in bioinformatics · 2015Article
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Authors and funding
4 authors.
Funding
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Abstract
Identification of protein binding sites is critical for studying the function of the proteins. In this paper, we proposed a method for protein binding site prediction, which combined the order profile propensities and hidden Markov support vector machine (HM-SVM). This method employed the sequential labeling technique to the field of protein binding site prediction. The input features of HM-SVM include the profile-based propensities, the Position-Specific Score Matrix (PSSM), and Accessible Surface Area (ASA). When tested on different data sets, the proposed method showed promising results, and outperformed some closely relative methods by more than 10% in terms of AUC.
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