Garmin Connect has a number of plots built in, but to take a deeper dive into all your fitness data, you need to export a CSV and fire up R. This post is a quick guide to some possibilities for running data.  There’s a few things that I wanted to look at. For example, how does my speed change through the year? How does that compare to previous years? If I see some trends, is that the same for short runs and long runs?

We have a new preprint out – it is a cautionary tale about using GFP nanobodies in cells. This short post gives a bit of background to the work. Please read the paper if you are interested in using GFP nanobodies in cells, you can find it here. Paper in a nutshell: Caution is needed when using GFP nanobodies because they can inhibit their target protein in cells.

Anyone that maintains a website is happy that people out there are interested enough to visit. Web traffic is one thing, but I take greatest pleasure in seeing quantixed posts being cited in academic papers. I love the fact that some posts on here have been cited in the literature more than some of my actual papers. It’s difficult to track citations to web resources.

Our lab is international. People born all over the world have come to work in my group. I’m proud of this fact, especially in the current political climate. I’ve previously used the GoogleMaps API to display a heat map on our lab webpage. It shows where in the world people in the lab come from. This was OK, but I wanted to get an R based solution to make this graphic to make it easier to automate updates.

I read this recent paper about very highly cited papers and science funding in the UK. The paper itself was not very good, but the dataset which underlies the paper is something to behold, as I’ll explain below. The idea behind the paper was to examine very highly cited papers in biomedicine with a connection to the UK. Have those authors been successful in getting funding from MRC, Wellcome Trust or NIHR?

This week Erick Martins Ratamero and I put up a preprint on vesicle packing. This post is a bit of backstory but please take a look at the paper, it’s very short and simple. The paper started when I wanted to know how many receptors could fit in a clathrin-coated vesicle. Sounds like a simple problem – but it’s actually more complicated.

I saw today on Twitter that a few labs were examining the gender balance of their papers and posting the ratios of male:female authors. It started with this tweet. This analysis is simple to perform, but interpreting it can be hard. For example, is the research group gender balanced to start with? How many of the authors are collaborators? Nonetheless, I have the data for all of my papers, so I thought I’d take a quick look too.

This is a quick “how to” post. There is a licensed version of PyMol (MacPyMol) available, but the open source version can be installed on a Mac free of charge. The official page has a guide, which is not terribly detailed, and I found this excellent guide which is unfortunately out-of-date.

On a whim a posted a plot on Twitter. It shows a marathon training schedule. This post explains the story behind the graph. I downloaded a few different 17-week marathon training schedules. Most were in imperial measurement and/or were written for time at a certain pace, e.g. 30 min Easy Run etc.

I really dislike being asked “how big is your lab?”. The question usually arises at scientific meetings when you are chatting to someone during a break. Small talk can lead to some banal questions being asked, and that’s fine, but when this question is asked seriously, the person asking really just wants to compare themselves to you in some way.

Since I have now written several posts on this. I thought I would summarise the computer-based tools that we are using in the lab to automate our work and organise ourselves.