The Bioinformatics Group at the Babraham Institute has experience in a wide variety of areas of bioinformatics including genomics, proteomics, statistics and microarrays as well as having extensive experience of custom software development.

The Bioinformatics group runs a regular series of training courses on many aspects of bioinformatics.

Where possible they also aim to make the material from their courses publicly available so that anyone who wants to can download them for their own use.

Here, is a list of those courses, providing training manual, course exercises and links for data download.


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Introduction to Python

Python has established itself as one of the most commonly used programming languages. It is a very powerful language, which makes it relatively easy to write programs from simple automation scripts to more fully featured applications. In bioinformatics python has become widely used both as a language to write scripts and applications, but also, via packages like pandas, numpy and seaborn as an environment for data analysis, competing with more focussed languages such as R. In this course we focus on the use of python to develop simple scripts and larger applications. These can be used for simple data processing and aggreagation, for automating repeated tasks or to write larger user-facing command line programs. We start from the ground up, and make no assumption of any previous programming experience.
Core Bioinformatics skills

Advanced Python

In recent years, the programming language Python has become ever more popular in the bioinformatics and computational biology communities and indeed, learning this language marks many people's first introduction to writing code. This success of Python is due to a number of factors. Perhaps most importantly for a beginner, Python is relatively easy to use, being what we term a "high-level" programming language. Don't let this terminology confuse you however: "high-level" simply means that much of the computational tasks are managed for you, enabling you to write shorter and simpler code to get your jobs done. This course builds on the basic features of Python3 introduced in the Introduction to Python course. At the end of this course you should be able to write moderately complicated programs, and be aware of additional resources and wider capabilities of the language to undertake more substantial projects. The course tries to provide a grounding in the basic theory you'll need to write programs in any language as well as an appreciation of the right way to do things in Python.
Core Bioinformatics skills

Python: Object Oriented Programming

A strength of Python and a feature that makes this language attractive to so many, is that Python is what is known as an object-oriented programming language (OOP). This is a short course that introduces the basic concepts of OOP. It then goes into more detail explaining how to build and manipulate objects. While this course does not provide an exhaustive discussion of OOP in Python, by the end of the course attendees should be able to build sophisticated objects to aid analysis and research.
Core Bioinformatics skills

Introduction to Unix

Increasing amounts of bioinformatics work is done in a command line unix environment. Most large scale processing applications are written for unix and most large scale compute environments are also based on this. This course provides an introduction to the concepts of unix and provides a practical introduction to working in this environment. Internally we link this course to a more specific course illustrating the use of our internal cluster environment and this part of the course could be adapted for other sites with different compute infrastructure
Core Bioinformatics skills

Learning to Program with Perl

For a long time, Perl has been a popular language among those starting out with programming. Although it is a powerful language, many of its features make it especially suited to first time programmers as it reduces the complexity found in many other languages. Perl is also one of the world's most popular languages which means there are a huge number of resources available to anyone setting out to learn it. This course aims to introduce the basic features of the Perl language. At the end you should have everything you need to write moderately complicated programs, and enough pointers to other resources to get you started on bigger projects. The course tries to provide a grounding in the basic theory you'll need to write programs in any language, as well as an appreciation for the right way to do things in Perl.
Core Bioinformatics skills

Introduction to Machine Learning

This course provides a theoretical and practical introduction to the use of machine learning on biological datasets. For the final section of the course we will introduce the tidymodels framework for machine learning in R, so it will be helpful to have attended our introductory and advanced R courses, or to have had equivalent experience, although this is not a prerequisite to attend the course.
Core Bioinformatics skills