… applications of machine learning to … machine learning on AMPs can be used to identify
essential physico-chemical determinants of AMP functionality, and identify and design peptide …

… machine learning to guide the sequence selection process. Our results demonstrate that
antimicrobial peptide … The proposed approach could be extended to peptide design with other …

… We demonstrate this by optimizing the efficacy of antimicrobial peptides (AMPs). In particular…
, machine learning, and in vitro evaluation to improve the antimicrobial activity of peptides …

… peptides. Finally, we discuss advances, limitations, and future directions of machine-learning
predictions of antimicrobial peptides. … of such predictions beyond antimicrobial activity to …

… original sequences as the inputs are seldomly used for training machine learning methods.
… In this article, we first provide a comprehensive survey on current machine learning-based …

… Machine learning (ML) consists of the recognition of patterns from training data and offers …
In the area of peptide drugs, ML is mostly being tested to design antimicrobial peptides (AMPs)…

… Machine learning has aided in the discovery … , antimicrobial activity), train a machine learning
model to predict that property using relatively easily obtained features (eg, primary peptide …

… cataloged in the Antimicrobial Peptide Database (APD) [5]… antimicrobial potential of new
sequences. In this paper, traditional ML refers to all ML methods such as support vector machine …

… machine learning tools to develop in silico models as AMP predictors. In this paper, we have
explored several machine learning … (k-NN) [1], Support Vector Machine (SVM) [6], Decision …

… In this study, we made an attempt to develop an advanced machine learning based computational
approach, MAMPs-Pred, for identification of AMPs and its function types. Initially, SVM-…