Antimicrobial Databases and Genotype Prediction: Data Sharing and Analysis

Duration: 3 weeks, 5 hours per week
Free Certificate of Achievement available on satisfactory completion

Start Date: The course is run ‘live’ for 3 weeks from 30th September 2024.  After this period, the course will remain open for completion for a further 6 weeks, but without facilitation by the educators.

Why join this course? 

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.

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.

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.

Who is this course for? 

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.

Course start dates

This course will start on 30th September 2024

What topics will you cover?

Week 1 What is AMR data and how is it created?

• Genetic basis for AMR
• Phenotypic data approaches
• Methods for linking genotypic with phenotypic evidence

Week 2 How do you detect AMR in your own data?

• AMR Databases
• Algorithms/Tools for detecting AMR
• Harmonisation of AMR outputs/databases

Week 3 What do we do with the data?

• Further analyses of AMR
• Why sharing is important?
• Principles of FAIR and open access data
• Databases for storing public data
• Where do we go next – AI/ML

Educators, Developers and Contributors 

Jane Hawkey

Jane is currently a research fellow at Monash University in the Infectious Disease Genomics @ Alfred group, where she focuses on developing our understanding of AMR in the hospital setting.de using WGS to study transmission in different bacterial species.

Kristy Horan 

Lead Bioinformatician AusTrakka platform. I have a keen interest translational AMR genomics and developing tools to deliver results that are actionable in a public and clinical health setting.

Education Developer

Dusanka Nikolic – Wellcome Connecting Science, UK

Coordinators
Katherine Kaldeli – Wellcome Connecting Science, UK

Zoey Willard – Wellcome Connecting Science, UK

International contributors

The Wellcome Connecting Science Learning and Training team are offering everyone who joins this course a free digital upgrade, so that you can experience the full benefits of studying online for free. This means that you get:

• Unlimited access to this course
• Includes any articles, videos, peer reviews and quizzes
• Tests to validate your learning
• A PDF Certificate of Achievement to prove your success when you’re eligible