I’ve previously crunched times for local Half and Full Marathons here on quantixed. Last weekend was the Kenilworth Half Marathon (2018) over a new course. I thought I’d have a look at the distributions of times and paces of the runners. The times are available here. If the Time and Category for finishers are saved […]
Rip It Up: Grabbing movies from Twitter for use in ImageJ
Some great scientific data gets posted on Twitter. Sometimes I want to take a closer look and this post describes a strategy to do so. Edit: I received a request to take down the 3D volume images derived from the example dataset I used in this post. I’ve edited the post below so that is […]
Ferrous: new paper on FerriTagging proteins in cells
We have a new paper out. It’s not exactly news, because the paper has been up on bioRxiv since December 2016 and hasn’t changed too much. All of the work was done by Nick Clarke when he was a PhD student in the lab. This post is to explain our new paper to a general […]
Pentagrammarspin: why twelve pentagons?
This post has been in my drafts folder for a while. With the World Cup here, it’s time to post it! It’s a rule that a 3D assembly of hexagons must have at least twelve pentagons in order to be a closed polyhedral shape. This post takes a look at why this is true. First, […]
Rollercoaster III: yet more on Google Scholar
In a previous post I made a little R script to crunch Google Scholar data for a given scientist. The graphics were done in base R and looked a bit ropey. I thought I’d give the code a spring clean – it’s available here. The script is called ggScholar.R (rather than gScholar.R). Feel free to […]
Ten Years vs The Spread: Calculating publication lag times in R
There have been several posts on this site about publication lag times. You can read them here. Lag times are the delays in the dissemination of scientific data introduced by the process of publishing the paper in a journal. Nowadays, your paper can be online in a few hours using a preprint server. However, this […]
Cloud Eleven: A cloud-based code sharing solution for IgorPro
This post is something of a “how to” guide. The problem is how can you share code with a small team and keep it up-to-date? For ImageJ, the solution is simple. You can make an ImageJ update site and then push any updated code to the user when they startup ImageJ. For IgorPro, there is […]
Rollercoaster II: more on Google Scholar citations
I’ve previously written about Google Scholar. Its usefulness and its instability. I just read a post by Jon Tennant on how to harvest Google Scholar data in R and I thought I would use his code as the basis to generate some nice plots based on Google Scholar data. A script for R is below […]
Turn That Heartbeat Over Again: comparing wrist and chest-strap HRM
As a geek, the added bonus of exercise is the fun that you can have with the data you’ve generated. A recent conversation on Twitter about the accuracy of wrist-based HRMs got me thinking… how does a wrist-based HRM compare with a traditional chest-strap HRM? Conventional wisdom says that the chest-strap is more accurate, but […]
I’m not following you II: Twitter data and R
My activity on twitter revolves around four accounts. I try to segregate what happens on each account, and there’s inevitably some overlap. But what about overlap in followers? What lucky people are following all four? How many only see the individual accounts? It’s quite easy to look at this in R. So there are 36 […]