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 […]
Category: publishing
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 […]
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 […]
Scoop: some practical advice
So quantixed occasionally gets correspondence from other researchers asking for advice. A recent email came from someone who had been “scooped”. What should they do? Before we get into this topic we have to define what we mean by being scooped. In the most straightforward sense being scooped means that an article appeared online before […]
In a Word: LaTeX to Word and vice versa
Here’s a quick tech tip. We’ve been writing papers in TeX recently, using Overleaf as a way to write collaboratively. This works great but sometimes, a Word file is required by the publisher. So how do you convert from one to the other quickly and with the least hassle? If you Google this question (as […]
Some Things Last A Long Time II
Back in 2014, I posted an analysis of the time my lab takes to publish our work. This post is very popular. Probably because it looks at the total time it takes us to publish our work. It was time for an update. Here is the latest version. The colours have changed a bit but […]
Fusion confusion: new paper on FGFR3-TACC3 fusions in cancer
We have a new paper out! This post is to explain what it’s about. Cancer cells often have gene fusions. This happens because the DNA in cancer cells is really messed up. Sometimes, chromosomes can break and get reattached to a different one in a strange way. This means you get a fusion between one […]
Parallel lines: new paper on modelling mitotic microtubules in 3D
We have a new paper out! You can access it here. The people This paper really was a team effort. Faye Nixon and Tom Honnor are joint-first authors. Faye did most of the experimental work in the final months of her PhD and Tom came up with the idea for the mathematical modelling and helped to […]
Tips from the blog XI: Overleaf
I was recently an external examiner for a PhD viva in Cambridge. As we were wrapping up, I asked “if you were to do it all again, what would you do differently?”. It’s one of my stock questions and normally the candidate says “oh I’d do it so much quicker!” or something similar. However, this time I […]
The Arcane Model
I’m currently writing two manuscripts that each have a substantial data modelling component. Some of our previous papers have included computer code, but it was straightforward enough to have the code as a supplementary file or in a GitHub repo and leave it at that. Now with more substantial computation in the manuscript, I was wondering how best to […]