
DOMAIN: LIFE SCIENCES
STATUS: STARTING TRL 2-3
USE CASE LEAD: CERTH

Deployment of AI agents to optimize molecular biodiversity research through automated data curation and processing, using AI agents, Large Language Models (LLMs), and taxonomic profiling tools.
The challenge
Metagenomic and biodiversity datasets are rapidly growing in volume and complexity but remain fragmented, inconsistently annotated, and difficult to integrate. Key metadata fields are often missing or mislabelled, limiting the reproducibility and comparability of analyses. Taxonomic profiles vary depending on the computational tools used, and valuable ecological insights are often buried in unstructured literature. Researchers face significant challenges in curating, organizing, and interpreting this information at scale. There is a clear need for intelligent, automated systems that can support data harmonisation across diverse sources.
The APPROACH
Automated Curation
AI-driven standardization of sample and taxonomic metadata across repositories.
Sample Classification
Categorizing samples into biomes using sequence patterns and metadata.
Taxonomic Integration
Reconciling data from multiple profilers for unified taxonomic results.
Literature Mining
Extracting microbiological insights from scientific papers via LLMs, echo park esse tilde. 90’s hammock do cupidatat, edison bulb mumblecore vape cloud bread.
Expected results
Metagenomic and biodiversity datasets are rapidly growing in volume and complexity but remain fragmented, inconsistently annotated, and difficult to integrate. Key metadata fields are often missing or mislabelled, limiting the reproducibility and comparability of analyses. Taxonomic profiles vary depending on the computational tools used, and valuable ecological insights are often buried in unstructured literature. Researchers face significant challenges in curating, organizing, and interpreting this information at scale. There is a clear need for intelligent, automated systems that can support data harmonisation across diverse sources.