This week we will be working with Python notebooks in the computing lab and learning about exploring data in the NCBI system. In the lecture this week I will be describing how we perform pairwise alignment and explaining what substitution (sic. scoring) matrices are, how they are made, and how we use them to help us when comparing different kinds of biological sequence. The last of the notebooks from the lab this week allows you to play with sequence alignment algorithms that are implemented in BioPython's Pairwise2 package.
Reading Lists & Resources
Each week we will have an accompanying reading list with some articles & web-sites for self study to support the course. You can find the course "Resource List" - here. We will continue to curate the list throughout the course especially if things pop up in the lectures and practicals that we want to add a reference or link to so do please check back in on the list from time to time.
We have generally tried to identify resources as "Essential", "Recommended" or "Further Reading" in an attempt to help you prioritise your reading during the course.
Finally a very important time to draw your attention to what you can consider the "core text" for the course, which is the excellent "Bioinformatics & Functional Genomics" Third Edition by Jonathan Pevsner. You will be pleased to know that this text-book is available free online as part of the University's subscription portfolio. You can find it right at the top of the resource list. If you have any problems accessing or using any of the above please do drop us a comment in the Discussion forum and we will try to get things resolved as soon as possible.
This week you should try to read Chapter 3 - "Pairwise Sequence Alignment" of BFG.
Lecture 2 - Pairwise Sequence Analysis
The lecture slides for Week 2 - "Pairwise Sequence Analysis" will be made available here.
The video of the lecture can be found here. You can also click the image below to view it directly on YouTube:
This week in the computing lab we will be working with some Python notebooks, the last one is for pairwise sequence analysis. You can access all of the computing lab materials on our GitHub page.
There are challenges at the end of the notebooks that you might like to have a go at. Please feel free to post in the Discussion board in the relevant section if you have any queries and/or comments. Please refrain from posting your solutions on there until we've had a chance to go through these.