SAGeSA Workshop: Evaluating Tools for AMR Detection & AI in Data Analysis
Date & Time: 25 April, 08:30 – 10:30 GMT (10:30 – 12:30 CAT)
Why Join This Workshop?
Learn how to critically evaluate antimicrobial resistance (AMR) predictions using Pathogenwatch and ResFinder, and integrate AI tools like ChatGPT for data analysis. Through hands-on exercises with real Staphylococcus aureus genomic data, you’ll compare bioinformatics tools, identify discrepancies, and assess the strengths and limitations of AI-driven methods.
Key Activities
- Tool Comparison: Analyze bacterial WGS data using multiple bioinformatics tools.
- Data Processing: Compare manual vs. AI-assisted AMR result analysis.
- AI Integration: Use ChatGPT to interpret AMR data and compare software outputs.
- Critical Assessment: Discuss AI’s role in bioinformatics—can it be trusted for decision-making?
Who Should Apply?
Researchers with a solid understanding of bacterial genomics and AMR. Familiarity with Python scripting is recommended but not required.
Learning Outcomes
- Use Pathogenwatch & ResFinder to analyze AMR genes.
- Compare AMR predictions from different bioinformatics tools.
- Use Python (Google Colab) for AMR result automation.
- Apply AI (ChatGPT) for data analysis and interpretation.
- Critique AI’s suitability for scientific data analysis.
Prerequisites
Trainers
Monica Abrudan – Wellcome Connecting Science, United Kingdom
Stanford Kwenda – National Institute for Communicable Diseases, South Africa
Apply Now!
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