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Table 2 The experimental results of various individual and combinative features on the training set for general BLPs

From: Prediction of bioluminescent proteins by using sequence-derived features and lineage-specific scheme

Type Feature Sensitivity Specificity Accuracy MCC AUC
Individual AACa 0.729 ± 0.029 0.806 ± 0.023 0.767 ± 0.020 0.537 ± 0.039 0.802 ± 0.012
DCb 0.791 ± 0.017 0.857 ± 0.028 0.824 ± 0.014 0.650 ± 0.029 0.830 ± 0.016
MTFc 0.313 ± 0.017 0.942 ± 0.012 0.628 ± 0.008 0.328 ± 0.018 0.653 ± 0.010
PCPd 0.452 ± 0.010 0.910 ± 0.026 0.681 ± 0.010 0.408 ± 0.029 0.763 ± 0.014
Combinative AAC + DC 0.799 ± 0.015 0.862 ± 0.026 0.830 ± 0.008 0.663 ± 0.018 0.841 ± 0.012
AAC + MTF 0.764 ± 0.016 0.801 ± 0.021 0.783 ± 0.005 0.566 ± 0.011 0.810 ± 0.007
AAC + PCP 0.728 ± 0.013 0.809 ± 0.013 0.768 ± 0.007 0.538 ± 0.015 0.813 ± 0.008
DC + MTF 0.799 ± 0.014 0.854 ± 0.008 0.826 ± 0.008 0.653 ± 0.015 0.836 ± 0.005
DC + PCP 0.775 ± 0.014 0.878 ± 0.020 0.827 ± 0.004 0.658 ± 0.009 0.841 ± 0.006
MTF + PCP 0.477 ± 0.010 0.917 ± 0.016 0.697 ± 0.004 0.440 ± 0.014 0.764 ± 0.020
AAC + DC + MTF 0.772 ± 0.007 0.888 ± 0.011 0.830 ± 0.008 0.665 ± 0.016 0.842 ± 0.006
AAC + DC + PCP 0.780 ± 0.007 0.880 ± 0.016 0.830 ± 0.009 0.663 ± 0.019 0.845 ± 0.009
AAC + MTF + PCP 0.742 ± 0.011 0.793 ± 0.004 0.767 ± 0.005 0.536 ± 0.010 0.816 ± 0.004
DC + MTF + PCP 0.775 ± 0.014 0.886 ± 0.025 0.830 ± 0.011 0.665 ± 0.023 0.845 ± 0.014
AAC + DC + MTF + PCP 0.770 ± 0.010 0.894 ± 0.014 0.836 ± 0.004 0.676 ± 0.010 0.850 ± 0.006
  1. The results are reported by maximizing the MCC value of prediction on the corresponding dataset over five-fold cross-validation. a indicates the features of amino acid composition; b stands for the features of dipeptide composition; c is the features of motifs; d represents the features of physicochemical properties