Computational Approaches to Decipher Microbiome–Host Interaction Networks

The intricate interplay between microbiomes and their hosts profoundly shapes health, disease, and evolution across diverse organisms. Recent advances in computational biology and bioinformatics have empowered researchers to untangle these complex networks, offering novel insights that traditional experimental techniques alone cannot provide.

This Research Topic aims to spotlight state-of-the-art computational and bioinformatic approaches for elucidating microbiome–host interactions. We invite submissions showcasing methodological innovations, integrative analyses, and novel applications that deepen our understanding of these multifaceted relationships.

Areas of interest include, but are not limited to:

o Multi-omics integration: Approaches that leverage metagenomics, metatranscriptomics, metabolomics, and other omics data to model host–microbe interactions at multiple molecular levels.

o Network-based modeling: Techniques to infer microbial community dynamics, host response pathways, and interaction networks.

o Machine learning and AI: Predictive models that unravel microbiome-mediated host phenotypes and outcomes, including applications of deep learning and statistical learning strategies.

o Computational tools: New software, pipelines, or algorithms for characterizing microbiome functional roles in health, disease, and therapeutics.

o Evolutionary and ecological perspectives: Methods that shed light on how microbiomes and their hosts adapt and co-evolve in changing environments.

We welcome original research articles, comprehensive reviews, methods papers, and perspectives that push the boundaries of computational biology in the context of microbiome–host interactions. By assembling a diverse range of contributions, this Topic seeks to foster cross-disciplinary dialogue and accelerate progress in this fascinating field.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: computational biology, bioinformatics, multi-omics integration, network modeling, machine learning, metagenomics, deep learning, evolutionary dynamics, microbial community analysis

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.