A quick post this week. I write “this week” in an attempt to convince regular readers that weekly posting will continue. I noticed that J. Cell Sci. give download metrics for their papers and that these downloads are categorised into abstract, full-text and PDF. I was interested in how one of my papers performed.

Around the globe, there are initiatives and organizations devoted to bring “Open Access” to the world, i.e., the public availability of scholarly research works, free of charge.

By now, it is public knowledge that subscription prices for scholarly journals have been rising beyond inflation for decades (i.e., the serials crisis): A superficially very similar graph was recently published for APC price increases: When not paying too much attention, both figures seem to indicate a linear increase in costs over time for both business models. However, the situation is more complicated than that.

At GigaScience as our focus is on reproducibility rather than subjective impact, it can be challenging at times to judge this in our papers. Targeting the “bleeding edge” of data-driven research, more and more of our papers utilise technologies, such as Jupyter notebooks, Virtual Machines, and Containers such as Docker.

There is an entertaining rumour going around about the journal Nature Communications . When I heard it for the fourth or fifth time, I decided to check out whether there is any truth in it. Sometimes it is put another way: cell biology papers drag down the impact factor of Nature Communications , or that they don’t deserve the high JIF tag of the journal because they are cited at lower rates. Could this be true?

Time for an update to a previous post. For the past few years, I have been using an automated process to track citations to my lab’s work on Google Scholar (details of how to set this up are at the end of this post). Due to the nature of how Google Scholar tracks citations, it means that citations get added (hooray!) but might be removed (booo!). Using a daily scrape of the data it is possible to watch this happening.

FAIRer Sharing via FAIRsharing Image from FAIRsharing.org. Our aim at GigaScience is to provide the means to open up and share research data. On top of just making these available via our (new look) GigaDB database, we’ve been involved with communities that wants to maximize the utility of these research outputs by making them FAIR: Findable, Accessible, Interoperable and Reusable.

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.

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?