We are involved in EBI’s newest resource, the AMR portal. This brings together
phenotypic AMR (often MIC) from the CABBAGE project
with genotype calls from AMRFinderPlus. We encourage users to download and reuse data from the resource.
We co-run the AllTheBacteria project with Zamin Iqbal.
The resources includes around 2.5M publicly available bacterial isolates, uniformly assembled and annotated. The
genomes are searchable, and community resources to expand the annotation are also available.
Written by Leonie Lorenz and Eva Geissen, this free online course will take you through
introductory concepts on the use of mathematical models for biological problems: doi:10.6019/TOL.maths-biologists-t.2025.00001.1
The course includes examples from both molecular biology and epidemiology.
This course which is aimed at helping improve programming skills of bioinformatics/computational biology graduate students and postdocs. The notes are self-contained and are freely available:
https://iprogramming.bacpop.org
They currently cover:
Optimising code
Running code efficiently on HPC systems
Compiled languages, data structures and object-oriented code
Software engineering techniques
From the intro:
This course/book is designed as your ‘second course’ in programming. It is assumed you’ve done a first course which taught you the basics of programming in an interpreted language (probably either python or R), and have now had some experience at using these in your research.
You might have felt that your code is holding you back, and that if you could make it faster or use less memory you could take your analysis further. Or you might have got a solution but are unsure whether it’s the right approach, or whether you could make it better.
Sometimes seeing the impressive (but sometimes intractable!) code and methods we use for research in bioinformatics can feel intimidating, and I feel there isn’t much formal guidance on how to engineer your code this way.
My hope is that this course will give you some extra skills and confidence when developing and improving your research code.
