Artificial intelligence (AI) and machine learning (ML) models are being deployed in many
domains of society and have recently reached the field of drug discovery. Given the …

The human gut microbiome encodes a large variety of antimicrobial peptides (AMPs), but
the short lengths of AMPs pose a challenge for computational prediction. Here we combined …

Antimicrobial peptides (AMPs) are emerging as a promising alternative to traditional
antibiotics due to their ability to disturb bacterial membranes and/or their intracellular …

Abstract Motivation Antimicrobial peptides (AMPs) are essential components of therapeutic
peptides for innate immunity. Researchers have developed several computational methods …

Antimicrobial peptides (AMPs) are a unique and diverse group of molecules that play a
crucial role in a myriad of biological processes and cellular functions. AMP-related studies …

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a
machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global …

Antibiotic resistance constitutes a global threat and could lead to a future pandemic. One
strategy is to develop a new generation of antimicrobials. Naturally occurring antimicrobial …

Antimicrobial peptides (AMPs) are a heterogeneous group of short polypeptides that target
not only microorganisms but also viruses and cancer cells. Due to their lower selection for …

Background The world faces a major infectious disease challenge. Interest in the discovery,
design, or development of antimicrobial peptides (AMPs) as an alternative approach for the …

Abstract Changes in the structure and function of the microbiota are associated with various
human diseases. These microbial changes can be mediated by antimicrobial peptides …