Visual Analytics to Understand COVID-19

William McNamara • June 1, 2020

How researchers are going to be looking to cure coronavirus

A few months ago, COVID-19 changed all of our lives by forcing much of the world into government-mandated lockdowns. Personally, the virus has impacted me and my family significantly, and I have a lot fo time since I can't leave my house, so I wanted to do what I could to try to understand the virus in my way. Hopefully you find this interesting and and if you're here that probably means you learn through visual analysis like me. So here we go!

When a virus like COVID-19 infects our cells, it's like a tiny hijacker taking over a factory. The virus sneaks its genetic instructions into our cells and forces them to make new virus parts; like the factory getting a new set of blueprints to make its products. These virus parts are initially made as long chains called polyproteins, which need to be cut into smaller, working proteins. COVID-19 has two special molecular scissors (called proteases) that do this cutting job. Scientists have captured detailed images of the main protease, giving it an identification number of 6LU7, you can read more about it here. In this post, I'll show you how to create different ways to visualize these proteases using a 3D graphics program called Blender.

First, we can write out the protease as a string of letters, where each letter represents a building block called an amino acid. While this might look like a jumbled alphabet soup, it's actually the complete instruction manual for building the proteases (the scissors).

Next, we can turn this string of letters into a graph, where each data point represents an amino acid, and lines show how they're connected. This helps us see patterns that weren't visible in the string of letters – some dots have many connections, suggesting they might be particularly important parts of the protease.

We can also create a bar graph showing how often each type of amino acid appears in the protease. In doing so we're taking inventory of all the parts needed to build it. Some amino acids might be used frequently, while others appear rarely.

Perhaps most excitingly, we can show the actual 3D shape of the protease. This 3D model helps researchers design drugs that might fit into specific pockets of the molecule, finding the right path to lock up the protein and stop the virus.

Each of these visualizations tells us something different about the same protease:

The letter sequence makes something invisible become visible
The graph reveals which parts might be especially important
The bar graph shows us which building blocks are used most often
The 3D model helps us understand where potential drugs might attach

By looking at the same object in different ways, we can discover new patterns and better understand how these proteases work. This understanding is crucial for developing treatments for COVID-19 and similar diseases.

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Fun with Spotify's API

By William McNamara • March 19, 2023

Like many music enthusiasts, the most used app on my phone by far is Spotify. One of my favorite features is their daily or weekly curated playlists based on your listening tastes. Spotify users can get as many as six curated ‘Daily Mixes’ of 50 songs, as well as a ‘Discover Weekly’ of 30 songs updated every Monday. That’s more than 2k songs a Spotify user will be recommended in a given week. Assuming an everage of 3 minutes per song, even a dedicated user would find themselves spending more than 15 hours a day to listen to all of that content. That…wouldn’t be healthy. But Spotify’s recommendations are good! And I always feel like I’m losing something when these curated playlists expire before I can enjoy all or even most of the songs they contain. Or at least I did, until I found a way around it. In this articule, I’m going to take you through Spotify’s API and how you can solve this problem with some beginner to intermediate Python skills. Introduction to Spotify’s API Spotify has made several public APIs for developers to interact with their application. Some of the marketed use cases are exploring Spotify’s music catalogue, queuing songs, and creating playlists. You can credential yourself using this documentation guide . I’d walk you through it myself but I don’t work for Spotify and I want to get to the interesting stuff. In the remainder of this article I will be talking leveraging Spotipy , an open source library for python developers to access Spotify’s Web API. NOTE : At the time of writing, Spotipy’s active version was 2.22.1, later versions may not have all of the same functionality available.