Agricultural and Life Sciences (IFAS)
Dias Lab
Led by Raquel Dias · Microbiology and Cell Science
What we study
The Dias Lab uses artificial intelligence to study diseases, combining data from microbes and hosts to predict and prevent illnesses. They focus on improving AI models and integrating genetic and environmental factors.
What working here is like
- Computational
- Bacteria & microbes
- Coding required
- Project
- 1
- Papers
- 5
Current projects
Bridging AI and Synthetic Biology for Engineering Thermally Resilient Bacteria
Uses AI together with synthetic biology to engineer bacteria that stay healthy at higher temperatures for industrial uses.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
Recent papers, explained
- The inflammatory path toward type 1 diabetes begins during pregnancy
2026 · Nature Communications
Finds early inflammatory markers linked to type 1 diabetes.
- A novel simulation tool for low-coverage whole-genome sequencing using multivariate Gaussian mixture models
2026 · BMC Bioinformatics
Develops a tool to simulate low-coverage genome sequencing data.
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- SpheronizaTor: Spherical Voxelization for Interpretable Protein Microenvironment Modeling
2026 · Computational and Structural Biotechnology Journal
Creates a new 3D model for protein environments to improve AI analysis.
- Early-life proteomic and microbiome features signal obesity risk across 26 years of follow-up
2026 · mSystems
Tracks childhood biomarkers to predict obesity risk over 26 years.
- Artificial intelligence‐powered plant phenomics: Progress, challenges, and opportunities
2025 · The Plant Phenome Journal
Reviews AI tools for plant phenomics and future research needs.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Raquel Dias hasn't set up this page yet. Their UF Scholars profile lists their publications.