| AMP |
ANTIMICROBIAL PEPTIDES |
| ML |
Machine Learning |
| STFT |
Short time Fourier transform |
| DL |
Deep Learning |
| MIC |
Minimum Inhibitory Concentrations |
| APD |
Antimicrobial Peptide Database |
| CNN |
Convolutional neural networks |
| RNN |
Recurrent neural networks |
| DRAMP |
Dragon Antimicrobial Peptide Database |
| CAMPR3 |
Cationic Antimicrobial Peptides Repository Version 3 |
| MARVIN |
Molecular Modeling and Visualization of Interactions in Neuropeptides |
| PCA |
Principal component analysis |
| NN |
Neural Network |
| KNN |
K Nearest Neighbor |
| NLP |
Natural language processing |
| Conv |
Convolution Layer |
| RELU |
rectified linear unit |
| Pool |
Pooling Layer |
| FC |
Fully connected |
| VGG |
Visual Geometry Group |
| ResNET |
Residual Networks |
| ROC |
Receiver Operating Characteristic |
| FN |
False Negatives |
| FP |
False Positive |
| TP |
True Positive |
| TN |
True Negative |
| DLP |
Deep learning prediction |
| MCC |
Matthews correlation coefficient |
| AUC |
Area under the curve |
| ACPs |
Antimicrobial Cationic Peptides |
