Author(s) :

Mohammed Azam.

Volume/Issue :

Abstract :

Bacteriophages, or phages, are viruses that specifically infect bacteria, and they have garnered attention as potential alternatives to antibiotics in the face of rising antimicrobial resistance (AMR). Understanding the complex interactions between bacteriophages and their bacterial hosts is fundamental to developing effective phage therapies. Traditional methods of studying phage-host relationships rely on empirical and experimental approaches, which are often time-consuming and labor-intensive. In contrast, machine learning models, particularly transformer-based deep learning models, have shown considerable promise in predicting these interactions by leveraging large datasets of genomic sequences. This paper explores the application of transformer models for predicting bacteriophage-host interactions, highlighting their potential benefits, challenges, and future directions in phage therapy and microbiome research.

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