Research in biology is increasingly dependent on computational approaches. However, the world of Computational Biology is big and confusing. This course aims to provide an introduction and map to that world, explaning what tools and techniques are out there and what you'll need to do to take advantage of them.
Next session: February 2018
The intended audience includes anyone interested in what Bioinformatics has to offer their research. We particularly welcome those who are completely new to the field.
Over the two sessions of this course, you'll learn about what's involved in modern bioinformatics. We'll explore the skills that are required in order to understand, plan and carry out bioinformatic analyses, manage data and interpret results. We'll also look at the resources you might need, as well as the things that can go wrong during bioinformatics.
By the end of the course, you should be able to understand which aspects of Bioinformatics might be beneficial to your research, what skills you'll need to acquire to actually realise that benefit, and realistic timescales for learning those skills.
The course will include a mixture of taught and practical material.
By the end of the course you should be able to:
Understand what Bioinformatics is, and how it can help biological research
Be able to plan which skills and resources you'll need for analyses you might want to carry out
Be aware of the pitfalls involved, and how to avoid or mitigate them
Know where to go to develop your learning further
Full course syllabus
Introduction - what is Bioinformatics, and why learn it?
Skills for bioinformatics - what do you need to learn in order to do Bioinformatics?
Building blocks to full analyses - what do we actually do in Computational Biology?
Resources - how big a computer do you really need?
When Bioinformatics goes bad - how things go wrong, and how to avoid it
Where next - further steps on the road to understanding