View on GitHub

ComputationalGenomicsManual

Robs manual for the computational genomics and bioinformatics class.

Introduction to Python

Jump to Learning Python

Python is one of the most popular programming languages. There are lots of reasons why, here are some of them.

The pros and cons of Python

Python is no where near the fastest computer programming language. In fact, it is even slower than some similar languages like Perl, but it is much easier to develop in Python than many other languages (e.g. Perl). In a lot of applications (e.g. bioinformatics, data science, geoscience), the development time is much more important than the computer run time. Note that you should still think about what affects computer run time and how to measure that, and sometimes you will run into intractable problems, but often the cheapest solution is to throw more computers at a problem, not to spend more time developing it. Note this is not always true, and there are many occassions (e.g. running things on cell phones) where you want to be very careful to optimize your applications!

Learning Python for Bioinformatics

We have adapted Marc Cohen’s Google Colab notebooks that teach Python to be more aligned with bioinformatics. This series of Python notebooks will walk you through the Python basics, and introduce you to more advanced concepts as you progress.

You can access the first Google Colab notebook here

Or you can jump to a specific lesson. Each of these links opens in Google Colab. You should make a copy of the file and run the code for yourself.