Artificial intelligence for exploring and understanding microbiomes

Microbiomes are complex ecosystems whose composition and dynamics shape the health of organisms and environments. Recent advances in artificial intelligence (AI) and machine learning have transformed our ability to interpret these communities from massive sequencing data. This webinar will explore how AI-driven models, ranging from statistical learning and neural networks to graph and language models, are being used to classify microbial communities, predict metabolic potential, and discover novel functions. We will discuss examples from metagenomic and metabolomic datasets that illustrate how AI can help us move from descriptive to predictive microbiome science, revealing hidden ecological and biochemical patterns across diverse habitats.

This webinar is part of the“Applications of artificial intelligence for biosciences in Latin America”webinar series, organised as part of theBiotrAIn project, a collaboration betweenUniversity of Costa Rica,CABANAnetand EMBL-EBI, funded by the Chan Zuckerberg initiative.

This webinar is delivered in Spanish. Synchronised captions are provided in both Spanish and English. The English translation has been automatically generated and is currently under review.

Outcomes

By the end of the webinar, you will be able to:

• Recall the main AI and machine learning approaches used in microbiome research, and recognise their applications to metagenomic, amplicon and metabolomic data.
• Identify opportunities to use AI tools for classification, functional prediction, and data integration in microbiome studies, as well as future trends in the field.
• Discuss how AI algorithms are applied in the study of microbiomes, antimicrobial resistance, and epidemiological data analysis.