About this Research Topic
At the frontier of biotechnology, bacteriophage biocontrol stands as a promising approach to address bacterial threats in diverse fields such as food safety, agriculture, medical and veterinary sectors. The surge in academic and practical interest in these areas underscores the potential of phages to revolutionize how bacterial infections can be confronted. Despite this promising opportunity, challenges related to phage-host interactions in these systems exist, including poor infection, limited host range and host resistance.
Moreover, optimization to improve such interactions are sometimes not considered. With the advent and development of technological tools such as artificial intelligence (AI) and machine learning, synthetic biology and biomaterial science, there remain more strategies than ever to inform the intelligent development of phage-based biocontrol strategies.
This research topic aims to explore how innovations in AI and machine learning, synthetic biology and biomaterials delivery can be leveraged to refine and enhance phage therapy. By transcending traditional methods, we aim to foster the development of more effective, adaptive, and scalable phage-based interventions. Empirical and theoretical contributions are sought to address the optimization of phage-host interactions, the overcoming of existing limitations, and the opening of new avenues for application in biocontrol.
In this topic we welcome submissions in the following sub-themes:
• Genetic engineering approaches for creating synthetic phages
• Predictive tools to elucidate phage-host dynamics
• Development of novel and high throughput pipelines for phage characterization
• Novel applications of phages involving both direct and indirect approaches for biocontrol
• Phage-based biomaterials development
• Analysis of virome datasets to uncover trends and novel genetic factors
• Transcriptomics studies aimed at elucidating phage-host interactions
• Regulatory framework and ethical considerations involving phage therapy
The article types considered for this Research Topic are Correction, Hypothesis & Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Review, Systematic Review, Technology and Code.
Moreover, optimization to improve such interactions are sometimes not considered. With the advent and development of technological tools such as artificial intelligence (AI) and machine learning, synthetic biology and biomaterial science, there remain more strategies than ever to inform the intelligent development of phage-based biocontrol strategies.
This research topic aims to explore how innovations in AI and machine learning, synthetic biology and biomaterials delivery can be leveraged to refine and enhance phage therapy. By transcending traditional methods, we aim to foster the development of more effective, adaptive, and scalable phage-based interventions. Empirical and theoretical contributions are sought to address the optimization of phage-host interactions, the overcoming of existing limitations, and the opening of new avenues for application in biocontrol.
In this topic we welcome submissions in the following sub-themes:
• Genetic engineering approaches for creating synthetic phages
• Predictive tools to elucidate phage-host dynamics
• Development of novel and high throughput pipelines for phage characterization
• Novel applications of phages involving both direct and indirect approaches for biocontrol
• Phage-based biomaterials development
• Analysis of virome datasets to uncover trends and novel genetic factors
• Transcriptomics studies aimed at elucidating phage-host interactions
• Regulatory framework and ethical considerations involving phage therapy
The article types considered for this Research Topic are Correction, Hypothesis & Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Review, Systematic Review, Technology and Code.
Keywords: bacteriophage, artificial intelligence, machine learning, predictive tools, automation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
