Deep Neural Networks Based on Sp7 Protein Sequence Prediction in Peri-Implant Bone Formation - Pradeep Kumar Yadalam; Carlos M. Ardila (International Journal of Dentistry)
Conclusion: The DNN employed with ADAM optimizer demonstrated robust performance in analyzing protein sequences, achieving an accuracy of 0.85 and high sensitivity and specificity. The ROC curve highlighted the model’s effectiveness in distinguishing true positives from false positives, which is essential for reliable protein classification. These findings suggest that the developed model is promising for enhancing predictive capabilities in computational biology and biomedical research, particularly in protein function prediction and therapeutic development applications.