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Function Prediction for DNA-/RNA-Binding Proteins, GPCRs, and Drug ADME-Associated Proteins by SVM

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This paper explores the use of support vector machine (SVM) for protein function prediction. Studies are conducted on several groups of proteins with different functions including DNA-binding proteins, RNA-binding proteins, Gprotein coupled receptors, drug absorption proteins, drug metabolizing enzymes, drug distribution and excretion proteins. The computed accuracy for the prediction of these proteins is found to be in the range of 82.32% to 99.7%, which illustrates the potential of SVM in facilitating protein function prediction.





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Keywords: DNA-binding proteins; G-protein coupled receptors (GPCRs); Protein function prediction; RNA-binding proteins; drug absorption proteins; drug distribution and excretion proteins; drug metabolizing enzymes; support vector machine (SVM)

Document Type: Research Article

Publication date: June 1, 2008

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  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
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