94 results about "Protein Feature" patented technology

The invention relates to a prediction method for protein subcellular site formed based on improved-period pseudo amino acid, which has a strategy that an integrated classifier is constructed with a KNN (K nearest neighbor) method and an SVM (support vector machine) method based on a one-to-one scheme. The prediction method aims to predict the protein subcellular site and accelerate protein function study and belongs to the field of bioinformatics. The prediction method is used for constructing the integrated classifier with the KNN method based on the Euclidean distance and the SVM method based on an RBF (radial basis function) kernel function. The protein characteristic information consists of improved-period pseudo amino acid and is obtained by the fact that a high-score characteristic closely related to the protein subcellular site is extracted with a fselect.py method on the basis of the characteristics of GO (gene ontology), AAC (amino acid composition), AAP (amino acid pair composition) and the hydrophily and the hydrophobicity of amino acid. The prediction accuracy of the protein subcellular site aims to be improved with two prediction methods of KNN and SVM and according to the high-score characteristic. In the implementation, the prediction method is identified from indexes, such as total prediction accuracy rate, each-site prediction accuracy rate, MCC (Markovian correlation coefficient) and the like with a jackknife inspection method. The prediction method disclosed by the invention is suitable for the prediction of the subcellular site of the proteins of different species.