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Metagenomic Analysis of Silage
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Artificial intelligence in microbial metagenomics.

Alisha Ansari1, Omprakash Shete1, Tarini Shankar Ghosh1

  • 1Department of Computational Biology, Indraprastha Institute of Information Technology, Delhi, India.

Progress in Molecular Biology and Translational Science
|April 15, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) and machine learning (ML) can analyze vast microbial genomics and metagenomic data. This review explores AI applications for biological questions and integrating multi-omics data, highlighting future potential.

Keywords:
Artificial intelligenceDeep learning and microbiome analysisMachine learningMetagenomics

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Data Science

Background:

  • Genomic sequencing generates massive amounts of microbial and microbiome data.
  • Data science, including AI, offers tools to analyze this complex biological information.
  • Researchers often struggle to find appropriate AI tools for specific microbial genomics questions.

Purpose of the Study:

  • To explore AI applications in microbial genomics and metagenomics using case studies.
  • To discuss AI/ML methods for integrating metagenomic data with other omics data.
  • To highlight the challenges and opportunities in AI-driven microbiome research.

Main Methods:

  • Review of AI methodologies applied to microbial genomics data.
  • Case study analysis of AI applications.
  • Discussion of AI/ML approaches for multi-omics data integration.

Main Results:

  • AI tools can address complex biological questions using microbial genomic and metagenomic data.
  • AI and ML facilitate the integration of metagenomic data with other omics datasets.
  • The field presents significant challenges and promising future possibilities.

Conclusions:

  • AI is crucial for unlocking insights from microbial genomics and metagenomic data.
  • Integrating multi-omics data with AI enhances biological understanding.
  • Continued development in AI offers vast potential for healthcare and industrial microbiology.