Computing Lab Materials

We will use this space to share the materials for the computing labs in weeks 2, 4, 6, and 8.

Course GitHub Site

In case people would prefer to pull the notebooks directly from GitHub, the course code is also hosted there:- https://github.com/tisimpson/bioinformatics1/tree/main/labs

Week 2 Computing Lab Materials

The notebook files can be downloaded from the GitHub site above, but are also available to download directly at the bottom of this page

Slides from the computing labs will be available here after the labs.

Remember that you can pull all of the code and data for this lab directly from the GitHub site which is by far the easiest way to do it. You can do this in Noteable by clicking the GitRepo button in the top-left of the window:-


Image showing location for GitHub repo cloning in notable

and pasting in the GitHub repositpory URL = https://github.com/tisimpson/bioinformatics1.git

I will post possible solutions from the Notebooks on here early next week to give everyone a chance to have a go at them beforehand. Please do post any questions to the Discussion Board in the "Python Coding Challenges & Questions" thread.

Week 4 Computing Lab Materials

There are two notebooks for this computing lab which you can find below as "BLAST" and "Multiple Sequence Alignment". They are also available from the course GitHub site.

You can also find the globins.fa file - here.

Week 6 Computing Lab Materials

The notebook for the week 6 lab is now available on the GitHub site - here. In this lab we will be programmatically accessing a variety of services holding biological data. These are based on the week5&6 notebooks so modification of the code there will help you complete the lab activities.

Week 8 Computing Lab Materials

The notebooks for the week 8 lab are now available on the GitHub site - part1 and part2. In this lab we will be programmatically accessing a variety of services holding biological data. These are based on the week7&8 lecture material for working with ontologies, enrichment analysis, and networks.

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