A Novel Sequence-Based Feature for the Identification of DNA-Binding Sites in Proteins Using Jensen–Shannon Divergence
Abstract
:1. Introduction
2. Results
2.1. Random Forest Classifier
2.2. Position Analysis of the MYC-MAX Protein
3. Materials and Methods
3.1. Materials
3.2. Methods
4. Discussion
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
Appendix A
Appendix A.1. Performance Measures with Standard Error
Feature | Sensitivity ± SE(%) | Specificity ± SE(%) | MCC ± SE(%) |
---|---|---|---|
29.2 ± 2.20 | 96.3 ± 0.46 | 30.7 ± 0.95 | |
+ | 38.5 ± 3.04 | 94.9 ± 0.57 | 34.9 ± 1.7 |
+ | 41.0 ± 3.23 | 93.9 ± 0.57 | 35.0 ± 1.85 |
+ + | 41.4 ± 3.42 | 94.0 ± 0.51 | 34.8 ± 2.07 |
+ | 33.9 ± 2.32 | 95.8 ± 0.37 | 33.4 ± 1.36 |
+ + | 41.6 ± 3.05 | 95.0 ± 0.46 | 37.8 ± 2.19 |
+ + | 44.1 ± 3.12 | 94.0 ± 0.43 | 37.2 ± 2.37 |
+ + + | 43.9 ± 3.14 | 94.0 ± 0.40 | 37.0 ± 2.25 |
+ + | 36.7 ± 2.07 | 96.8 ± 0.27 | 39.8 ± 1.58 |
+ + + | 42.2 ± 2.70 | 95.8 ± 0.42 | 40.9 ± 1.95 |
+ + + | 44.7 ± 3.05 | 95.0 ± 0.38 | 40.3 ± 1.98 |
+ + + + | 44.4 ± 3.12 | 94.7 ± 0.39 | 39.3 ± 2.02 |
Feature | Sensitivity ± SE(%) | Specificity ± SE(%) | MCC ± SE(%) |
---|---|---|---|
28.6 ± 2.56 | 96.6 ± 0.47 | 35.0 ± 1.43 5 | |
+ | 39.5 ± 2.89 | 95.0 ± 0.55 | 40.7 ± 1.99 |
+ | 41.8 ± 3.02 | 94.3 ± 0.62 | 41.1 ± 2.05 |
+ + | 42.6 ± 3.25 | 94.2 ± 0.54 | 41.4 ± 2.37 |
+ | 33.4 ± 2.34 | 96.3 ± 0.38 | 38.6 ± 1.90 |
+ + | 42.4 ± 2.97 | 95.1 ± 0.61 | 43.6 ± 2.43 |
+ + | 44.8 ± 2.99 | 94.4 ± 0.56 | 43.8 ± 2.45 |
+ + + | 44.5 ± 3.04 | 94.4 ± 0.50 | 43.4 ± 2.35 |
+ + | 33.7 ± 2.48 | 97.5 ± 0.35 | 43.1 ± 2.05 |
+ + + | 41.9 ± 2.89 | 95.8 ± 0.55 | 45.0 ± 2.39 |
+ + + | 43.9 ± 2.89 | 95.2 ± 0.48 | 45.3 ± 2.32 |
+ + + + | 44.2 ± 2.91 | 94.9 ± 0.54 | 44.5 ± 2.24 |
Appendix A.2. RBscore Dataset Analysis
Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|
0.458 | 0.974 | 0.476 | 0.866 | 0.460 | |
+ | 0.56 | 0.965 | 0.514 | 0.894 | 0.518 |
+ | 0.597 | 0.957 | 0.511 | 0.899 | 0.523 |
+ + | 0.591 | 0.958 | 0.511 | 0.90 | 0.526 |
+ | 0.512 | 0.97 | 0.501 | 0.878 | 0.476 |
+ + | 0.581 | 0.96 | 0.511 | 0.899 | 0.520 |
+ + | 0.611 | 0.953 | 0.508 | 0.903 | 0.526 |
+ + + | 0.613 | 0.953 | 0.509 | 0.902 | 0.528 |
+ + | 0.517 | 0.976 | 0.534 | 0.896 | 0.528 |
+ + + | 0.58 | 0.967 | 0.54 | 0.907 | 0.543 |
+ + + | 0.612 | 0.963 | 0.546 | 0.910 | 0.551 |
+ + + + | 0.601 | 0.962 | 0.531 | 0.909 | 0.546 |
Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|
0.445 | 0.977 | 0.528 | 0.873 | 0.589 | |
+ | 0.553 | 0.968 | 0.579 | 0.899 | 0.643 |
+ | 0.57 | 0.962 | 0.572 | 0.900 | 0.642 |
+ + | 0.569 | 0.963 | 0.574 | 0.895 | 0.642 |
+ | 0.49 | 0.973 | 0.547 | 0.880 | 0.602 |
+ + | 0.578 | 0.963 | 0.583 | 0.902 | 0.648 |
+ + | 0.605 | 0.958 | 0.587 | 0.904 | 0.652 |
+ + + | 0.603 | 0.959 | 0.587 | 0.902 | 0.653 |
+ + | 0.499 | 0.98 | 0.584 | 0.895 | 0.641 |
+ + + | 0.57 | 0.968 | 0.595 | 0.908 | 0.661 |
+ + + | 0.592 | 0.965 | 0.60 | 0.908 | 0.665 |
+ + + + | 0.594 | 0.964 | 0.597 | 0.907 | 0.663 |
Appendix A.3. PreDNA Dataset Analysis
Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|
0.378 | 0.977 | 0.41 | 0.840 | 0.391 | |
+ | 0.498 | 0.963 | 0.448 | 0.865 | 0.453 |
+ | 0.543 | 0.953 | 0.445 | 0.869 | 0.451 |
+ + | 0.538 | 0.956 | 0.453 | 0.869 | 0.455 |
+ | 0.393 | 0.975 | 0.417 | 0.847 | 0.402 |
+ + | 0.501 | 0.966 | 0.461 | 0.872 | 0.463 |
+ + | 0.545 | 0.959 | 0.465 | 0.876 | 0.468 |
+ + + | 0.523 | 0.958 | 0.449 | 0.875 | 0.465 |
+ + | 0.428 | 0.977 | 0.458 | 0.867 | 0.451 |
+ + + | 0.511 | 0.97 | 0.488 | 0.885 | 0.488 |
+ + + | 0.539 | 0.962 | 0.475 | 0.888 | 0.488 |
+ + + + | 0.539 | 0.961 | 0.47 | 0.886 | 0.488 |
Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|
0.373 | 0.979 | 0.463 | 0.833 | 0.496 | |
+ | 0.485 | 0.962 | 0.495 | 0.858 | 0.540 |
+ | 0.496 | 0.953 | 0.475 | 0.858 | 0.534 |
+ + | 0.495 | 0.955 | 0.479 | 0.857 | 0.535 |
+ | 0.389 | 0.977 | 0.47 | 0.839 | 0.501 |
+ + | 0.49 | 0.963 | 0.501 | 0.863 | 0.550 |
+ + | 0.503 | 0.957 | 0.492 | 0.865 | 0.547 |
+ + + | 0.504 | 0.958 | 0.497 | 0.865 | 0.550 |
+ + | 0.395 | 0.98 | 0.488 | 0.858 | 0.530 |
+ + + | 0.48 | 0.968 | 0.511 | 0.874 | 0.563 |
+ + + | 0.506 | 0.962 | 0.51 | 0.873 | 0.560 |
+ + + + | 0.499 | 0.96 | 0.498 | 0.871 | 0.555 |
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Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|
0.292 | 0.963 | 0.307 | 0.777 | 0.313 | |
+ | 0.385 | 0.949 | 0.349 | 0.795 | 0.369 |
+ | 0.41 | 0.939 | 0.35 | 0.802 | 0.377 |
+ + | 0.414 | 0.94 | 0.348 | 0.800 | 0.376 |
+ | 0.339 | 0.958 | 0.334 | 0.794 | 0.338 |
+ + | 0.416 | 0.95 | 0.378 | 0.808 | 0.390 |
+ + | 0.441 | 0.94 | 0.372 | 0.817 | 0.401 |
+ + + | 0.439 | 0.94 | 0.37 | 0.814 | 0.399 |
+ + | 0.367 | 0.968 | 0.398 | 0.838 | 0.413 |
+ + + | 0.422 | 0.958 | 0.409 | 0.837 | 0.425 |
+ + + | 0.447 | 0.95 | 0.403 | 0.841 | 0.431 |
+ + + + | 0.444 | 0.947 | 0.393 | 0.835 | 0.423 |
Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|
0.286 | 0.966 | 0.350 | 0.778 | 0.425 | |
+ | 0.395 | 0.95 | 0.407 | 0.801 | 0.487 |
+ | 0.418 | 0.943 | 0.411 | 0.807 | 0.494 |
+ + | 0.426 | 0.942 | 0.414 | 0.807 | 0.497 |
+ | 0.334 | 0.963 | 0.386 | 0.796 | 0.455 |
+ + | 0.424 | 0.951 | 0.436 | 0.814 | 0.513 |
+ + | 0.448 | 0.944 | 0.438 | 0.820 | 0.520 |
+ + + | 0.445 | 0.944 | 0.434 | 0.819 | 0.521 |
+ + | 0.337 | 0.975 | 0.431 | 0.830 | 0.517 |
+ + + | 0.419 | 0.958 | 0.450 | 0.832 | 0.535 |
+ + + | 0.439 | 0.952 | 0.453 | 0.836 | 0.539 |
+ + + + | 0.442 | 0.949 | 0.445 | 0.832 | 0.535 |
Cut-Off | Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|---|
3.5 Å | + + | 0.517 | 0.976 | 0.534 | 0.896 | 0.528 |
+ + + | 0.58 | 0.967 | 0.54 | 0.907 | 0.543 | |
+ + + | 0.612 | 0.963 | 0.546 | 0.910 | 0.551 | |
+ + + + | 0.601 | 0.962 | 0.531 | 0.909 | 0.546 | |
5.0 Å | + + | 0.499 | 0.98 | 0.584 | 0.895 | 0.641 |
+ + + | 0.57 | 0.968 | 0.595 | 0.908 | 0.661 | |
+ + + | 0.592 | 0.965 | 0.60 | 0.908 | 0.665 | |
+ + + + | 0.594 | 0.964 | 0.597 | 0.907 | 0.663 |
Cut-Off | Feature | Sensitivity | Specificity | MCC | AUC-ROC | AUC-PR |
---|---|---|---|---|---|---|
3.5 Å | + + | 0.428 | 0.977 | 0.458 | 0.867 | 0.451 |
+ + + | 0.511 | 0.97 | 0.488 | 0.885 | 0.488 | |
+ + + | 0.539 | 0.962 | 0.475 | 0.888 | 0.488 | |
+ + + + | 0.539 | 0.961 | 0.47 | 0.886 | 0.488 | |
5.0 Å | + + | 0.395 | 0.98 | 0.488 | 0.858 | 0.530 |
+ + + | 0.48 | 0.968 | 0.511 | 0.874 | 0.563 | |
+ + + | 0.506 | 0.962 | 0.51 | 0.873 | 0.560 | |
+ + + + | 0.499 | 0.96 | 0.498 | 0.871 | 0.555 |
Protein | Feature | Sensitivity | Specificity | MCC |
---|---|---|---|---|
MYC | + + | 0.30 | 0.941 | 0.282 |
+ + + | 0.70 | 0.853 | 0.448 | |
+ + + | 0.70 | 0.853 | 0.448 | |
+ + + + | 0.70 | 0.868 | 0.470 | |
MAX | + + | 0.222 | 1.0 | 0.447 |
+ + + | 0.888 | 0.906 | 0.664 | |
+ + + | 0.888 | 0.922 | 0.697 | |
+ + + + | 0.889 | 0.922 | 0.697 |
© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Dang, T.K.L.; Meckbach, C.; Tacke, R.; Waack, S.; Gültas, M. A Novel Sequence-Based Feature for the Identification of DNA-Binding Sites in Proteins Using Jensen–Shannon Divergence. Entropy 2016, 18, 379. https://doi.org/10.3390/e18100379
Dang TKL, Meckbach C, Tacke R, Waack S, Gültas M. A Novel Sequence-Based Feature for the Identification of DNA-Binding Sites in Proteins Using Jensen–Shannon Divergence. Entropy. 2016; 18(10):379. https://doi.org/10.3390/e18100379
Chicago/Turabian StyleDang, Truong Khanh Linh, Cornelia Meckbach, Rebecca Tacke, Stephan Waack, and Mehmet Gültas. 2016. "A Novel Sequence-Based Feature for the Identification of DNA-Binding Sites in Proteins Using Jensen–Shannon Divergence" Entropy 18, no. 10: 379. https://doi.org/10.3390/e18100379