Antimicrobial Databases and Genotype Prediction: Data Sharing and Analysis

Discover how to harness AMR genotype-phenotype databases to advance your career

Transform your understanding of antimicrobial resistance (AMR) and elevate your research or clinical practice with this online course from Wellcome Connecting Science.

Dive into the world of AMR genotype-phenotype databases and gain practical skills that will set you apart in your field.

Unlock the power of AMR data

On this course, you’ll learn how to effectively utilise antimicrobial resistance (AMR) genotype-phenotype databases to advance your research, clinical practice, and public health efforts. You’ll begin by understanding how AMR data is created and how these insights can enhance your work. This foundational knowledge will empower you to interpret AMR data with confidence and clarity.

Detect and analyse AMR in your data

After grasping data creation, you’ll discover how to effectively detect AMR in your own data using various tools and algorithms. You’ll learn to navigate AMR databases, understand their strengths and limitations, and harmonise outputs from different sources.

Share and leverage AMR data for impact

Next, you’ll learn how to share AMR data and understand how to do it in a FAIR (Findable, Accessible, Interoperable, Reusable) manner. At this point, you’ll also discuss the principles of open access data and explore databases for storing public data, as well as delving into future trends, including AI and machine learning, and how they are furthering AMR research and application.

Enhance your career prospects in the scientific arena

By the end of the course, you’ll be able to confidently contribute to AMR genotype-phenotype databases, improving your career mobility and making a tangible impact in your field.

You’ll join a global network of scientists and professionals dedicated to advancing AMR research and practice.

This course is designed for early career researchers, healthcare professionals at any stage, and public health experts who are familiar with AMR but have limited experience with genotypic data.

No advanced prior knowledge is required, just a basic understanding of AMR concepts and a desire to enhance your expertise.

• What is AMR data and how is it created?
• Introduction to Week 1
• Why do we care? Genetic basis for AMR
• Phenotypic data approaches
• Methods for linking genotypic with phenotypic evidence
• Future of linking geno and pheno including Machine Learning
• Your learning progress
• How do you detect AMR in your own data?
• Databases
• Algorithms/Tools for detecting AMR
• Issues and patterns
• Harmonisation of AMR outputs/databases
• Your learning progress
• What do we do with the data?
• Further analysis of AMR
• AMR epidemiology
• Equitable access and sharing
• How do I contribute?
• Where do we go next?
• Your learning outcomes