Biopython is a python library to handle Biological Data.

Biopython provides a set of tools to perform bioinformatics computations on biological data such as DNA data and protein data. I have been using Biopython ever since I started studying bioinformatics and it has never let me down with its functions. It is an amazing library which provides a wide range of functions from reading large files with biological data to aligning sequences. In this article, I will introduce you to some basic functions of Biopython which can make implementations much easier.

To install Biopython and to run the Biopython Codes we will use a a web IDE for python called as Google Colaboratory.

Google Colab is an excellent tool for deep learning tasks. It is a hosted Jupyter notebook that requires no setup and has an excellent free version, which gives free access to Google computing resources such as GPUs and TPUs.

Google Colab supports Python (and as of October 2019 only allows the creation of Python 3 notebooks), though in some cases with further tinkering it might be possible to get R, Swift, or Julia to work.

Have in mind that since the 1st January 2020, Python 2 is no longer supported.

There are several ways to get started with Google Colab and we will go over each of them. All approaches are quite easy and it depends on what you want to start working on (i.e. fresh notebook or GitHub repository).

The first way is to go over to your Google Drive account. In the top left corner select “New”, then “More” in the drop-down panel, and then “Google Collaboratory”.