Table 6.
Antimicrobial peptides prediction server developed in past 5 years (2015–2020)
| Server | Function | Year | URL | References |
|---|---|---|---|---|
| ADAM | SVM | 2015 | http://bioinformatics.cs.ntou.edu.tw/adam/tool.html | Lee et al. (2015) |
| Antimicrobial Peptide Database (APD3) | Parameter space | 2016 | http://aps.unmc.edu/AP/ | Guangshun Wang (2016) |
| CAMP | RF, SVM, Dragonfly algorithm (DA) | 2016 | www.bicnirrh.res.in/antimicrobial | Waghu et al. (2014) |
| Antimicrobial Activity Prediction (AMAP) | SVM, Shapley Additive explanation (SHAP), t-distributed Stochastic Neighbor Embedding (t-SNE) | 2019 | http://faculty.pieas.edu.pk/fayyaz/software.html#AMAP | Gull et al. (2019) |
| Integrative Antimicrobial Peptides Evaluator (IAMPE) | Naïve Bayes (NB), KNN, SVM, RF, eXtreme Gradient Boosting (XGBoost) | 2020 | http://cbb1.ut.ac.ir/ | Kavousi et al. (2020) |
| Deep-AmPEP30 | Convolutional neural network (CNN), reduced AAC (RAAC) | 2020 | https://cbbio.cis.um.edu.mo/AxPEP | Yan et al. (2020) |