RMSD Protein Tertiary Structure Prediction with Soft Computing
Автор: Mohammad Saber Iraji, Hakimeh Ameri
Журнал: International Journal of Mathematical Sciences and Computing(IJMSC) @ijmsc
Статья в выпуске: 2 vol.2, 2016 года.
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Root-mean-square-deviation (RMSD) is an indicator in protein-structure-prediction-algorithms (PSPAs). Goal of PSP algorithms is to obtain 0 Å RMSD from native protein structures. Protein structure and RMSD prediction is very essential. In 2013, the estimated RMSD proteins based on nine features were obtained best results using D2N (Distance to the native). We presented in This paper proposed approach to reduce predicted RMSD Error Than the actual amount for RMSD and calculate mean absolute error (MAE), through feed forward neural network, adaptive neuro fuzzy method. ANFIS is achieved better and more accurate results.
Root-mean-square-deviation (RMSD), protein, native structure, neural network, fuzzy
Короткий адрес: https://sciup.org/15010206
IDR: 15010206
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