PMC:4331676 / 31256-32080 JSONTXT

{"project":"2_test","denotations":[{"id":"25708928-19385697-14842664","span":{"begin":228,"end":230},"obj":"19385697"}],"text":"Table 3 shows the predictive results of SVM-PSSM-DT and four other state-of-the-art methods on the benchmark dataset through jackknife validation, including DNAbinder(dimension 21) [21], DNAbinder(dimension 400) [21], DNA-Port [74] and iDNA-Prot [16]. DNAbinder(dimension 21) and DNAbinder(dimension 400) encode features from their PSSM based evolutionary information and utilize SVM to build prediction model. iDNA-Prot applies grey model to integrate the features from protein sequence into the general form of pseudo amino acid composition and then inputs into a Random Forest classifier. DNA-Prot is a Random Forest classifier based on the amino acid composition, predicted second structure and some physicochemical properties. The ROC curves of the proposed method and the four predictive methods are shown in Figure 4."}