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Figure 1 | BMC Bioinformatics

Figure 1

From: Application of nonnegative matrix factorization to improve profile-profile alignment features for fold recognition and remote homolog detection

Figure 1

ROC scores of various methods for fold recognition at the fold level. The x-axis represents the ROC score and the y-axis represents the proportion of proteins with better performance than the corresponding ROC score. NMF, Original PPA, HHsearch, and PSI-BLAST denote SVM with NMF features, original PPA features, HMM-HMM alignment method, and PSI-BLAST, respectively. The results show that NMF features greatly improve the performance of fold recognition. The mean ROC score of NMF feature is 0.91, while those of original PPA feature, HHsearch, and PSI-BLAST are 0.82, 0.80, and 0.59, respectively.

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