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 […]
Category: publishing
One With The Freaks – very highly cited papers in biology
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 […]
All That Noise: The vesicle packing problem
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 […]
A Certain Ratio: Gender ratio in our papers
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 […]
For What It’s Worth: Influence of our papers on our papers
This post is about a citation analysis that didn’t quite work out. I liked this blackboard project by Manuel Théry looking at the influence of each paper authored by David Pellman’s lab on the future directions of the Pellman lab. I'm working on a new project for @criparis students: "The Tree of a Lab"= how […]
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 […]
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 […]
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 […]