Certificate of Achievement
has completed the following course:
Antimicrobial Databases and Genotype Prediction: Data Sharing and Analysis
This course covered antimicrobial resistance databases, the origin and forms of data they contain, how they are used for research and public health and the ways we can contribute to them.
3 weeks, 5 hours per week
Dr Treasa Craven
Head of Scientific Meetings and Digital Learning
Wellcome Sanger Institute
Dr Conor Meehan
Associate Professor of Microbial Bioinformatics
Nottingham Trent University, UK
Transcript
Learning outcomes
- Explain the genotypic basis of AMR
- Contrast and critique the various ways to predict AMR from linked genotype/phenotype data
- Discuss the various AMR databases and their related pros and cons
- Explain how different AMR prediction tools can be operated and their outputs interpreted and implemented, understanding the current pitfalls of those tools
- Describe the process required to create and share FAIR and open AMR data
Syllabus
What is AMR data and how is it created?
- Genetic basis for AMR
- Phenotypic data approaches
- Methods for linking genotypic with phenotypic evidence
How do you detect AMR in your own data?
- AMR Databases
- Algorithms/Tools for detecting AMR
- Harmonisation of AMR outputs/databases
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
In association with
Issued on 12th October 2024
The person named on this certificate has completed the activities in the transcript above. For more information about Certificates of Achievement and the effort required to become eligible, visit futurelearn.com/proof-of-learning/certificate-of-achievement.
This certificate represents proof of learning. It is not a formal qualification, degree, or part of a degree.
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