Monthly Archives: March 2023

HackDay: Data on Acid

Every year the (SSI) run a brilliant meeting called the , usually in Oxford. This is an lasting two days. At first glance it doesn’t look like it would be relevant to my research, but I always learn something new, meet interesting people and start, well, collaborations. The latest edition was last week and was the fourth I’ve attended. (Disclaimer: for the last year-and-a-bit I’ve been which has been very useful – this is how I managed to train up to be a Software Carpentry Instructor. Alas my tenure has now ended).

For the last two years the workshop has been followed by a hackday which I’ve attended. Now I’m not a software developer, I’m a research scientist who uses million-line community-developed codes (like GROMACS and NAMD), but I do write code, often python, to analyse my simulations and also to automate my workflows. A hackday therefore, where many of the participants are research software engineers, pushes me clear out of my comfort zone. I remember last year trying to write python to access GitHub using its and thinking “I’ve never done anything like this before and I’ve no idea what to do.�?. This year was no different, except I’d pitched the idea so felt responsible for the success of the project.

The name of the project, , was suggested by Boris Adryan and the team comprised myself, , , and . The input was data produced by a proof of principle project I’ve run to test if I can predict whether individual mutations to S.aureus DHFR cause resistance to trimethoprim. The idea was to then turn it into abstract forms, either visual or sound, so you can get an intuitive feel for the data. Or it could just be aesthetic.

To cut a long story short, we did it, it is up and we came third in the competition! In the long term I’d like to develop it further and incorporate it into my volunteer crowd-sourced project, , that aims to predict whether bacterial mutations cause antibiotic resistance or not (when it is funded that is).

Lectures, Clickers and Quizzes

It’s 9.40am. You are sitting in a nice warm lecture theatre. There are no windows. The lecturer is talking, their slides projected onto a big screen. You’re feeling sleepy but this course doesn’t seem too hard – you can always learn the key concepts from the lecture notes before the exams. And so in May and the exams are looming and it is warm and sunny, you drag yourself into the library, pull out the lecture notes (which seemed so clear in the lecture) and, wait, what is this nonsense? It makes no sense…

There is a trap here; what was appearing to make sense in the lecture hasn’t been learnt properly, by which I mean sufficiently embedded in the brain of our student that they can remember and, hopefully, understand the central concepts. Everything in the lecture is set up for you to learn the material there and then. The risk, then, is that it almost-but-doesn’t-quite penetrate the grey matter and so gradually all that knowledge slowly evaporates…

As you can probably tell I believe you either understand the topic in the lecture, or not at all. So what can I, the lecturer, do to help?

I believe encouraging the students to think helps their recall and one way to do this is to get them to answer a question. It doesn’t have to be difficult, but I think you do have to ask it shortly after you’ve explained the concept so it is still fresh in their mind.

To do this I tried using clickers this year. These are small on; each student gets one and then the lecturer, using special software on their laptop, puts a question on the screen and then they have to choose an answer. The results are then displayed on a graph and you can discuss which answer was correct and why.

An obvious barrier to using clickers is you have to buy them. So in previous years I have tried using a website, , and then asking the students to connect to it using their smartphones. But not everyone has a smartphone, which is unfair, and having to get on the wireless network, find the website etc which makes it clunky.

I aimed have a quiz half-way through each lecture (this is also a change and should therefore help their attention after the quiz) and another one at either the end, or occasionally, the beginning. Each quiz was very simple; between 6 and 10 simple statements to which they had to decide whether they were true or false. Very occasionally I would try and catch them out to illustrate a common misconception.

Two comments:

Using the clickers to do questions was very useful to assess [our] understanding as we went along.

The clickers are sick.

Some more quantitative feedback:

  • “The clickers were easy to use�?. (96% agreed)
  • “The quizzes helped me remember the key concepts from each lecture�? (95% agreed)
  • “I’d like more lectures to use clickers for quizzes�? (90% agreed)

So I’m going to view the clickers as a success.

New publication: Nothing to Sneeze At – A Dynamic and Integrative Computational Model of an Influenza A Virion

In this paper we show how we built and then simulated a model of the influenza A virion. Rather than model every atom of every lipid, a “coarse-grained�? representation () is instead used which replaces roughly every four atoms by a single coarse-grained bead. Microsecond simulations then start to give us insight into how the surface proteins move and whether they cluster. For these simulations we used the PRACE supercomputer, CURIE, which is based in France. I’ve previously posted some scaling data on the different PRACE machines – the system used was not the virion but is similar in size.

With a system of this size and complexity just creating the initial set of coordinates is a challenge. My part in this project was to develop a new method for inserting the surface proteins into the lipids. This method is currently under review at another journal and I will update this blog post when it is published.

The paper is free to download and you can find it .

Oh, and this makes three papers in the journal in the last eight months which is new PB.