The aim of this post is to look at revisions of bioRxiv preprints. I’m interested how long preprint versions exist on bioRxiv. In other words: how long do revisions to preprints take? The data from bioRxiv is a complex dataset with many caveats as I’ll explain further down, but some interesting details do emerge. Consider this a sketch of the dataset rather than an in-depth analysis. I’ll walk you through the code.

Some ideas about how the peer review process in academic publishing can be used as a device for preregistering parts of an empirical analysis.

This post is an update of a previous analysis on quantixed. We have covered publication lag times – the time it takes for a paper go from submitted (received) to accepted and published – a lot on here. It is possible to look at lag times, in R using data from PubMed. Previously my code performed these calculations using an XML file downloaded from the PubMed website.

As the COVID-19 pandemic continues, different countries are experiencing various restrictions including lockdowns. Some of these restrictions alter our ability to do science: by hindering lab access or taking time away from researchers for homeschooling. So, what impact has the pandemic had on scientific output? One way to look at this – for biology – is to look at newly deposited papers on bioRxiv.

The academic journal publishing system sure feels all too often a bit like a sinking boat: we have a reproducibility leak an affordability leak a functionality leak a data leak a code leak an interoperability leak a discoverability leak a peer-review leak a long-term preservation leak a link rot leak an evaluation/assessment leak a data visualization leak … … … and even a tiny access leak still remains even after 30 years of trying to fix it.

We have a new paper out! I am a bit late with this post, since the accepted version went online in December 2020, and the final version appeared a few weeks ago. It will shortly appear in a finished issue of the journal so I can tell myself that I am not too late yet. What’s it about? A complex of TACC3-chTOG-clathrin-GTSE1 is important for stabilising the mitotic spindle during cell division.

Looking back at this unusual COVID-dominated year, we are happy to report that GigaScience not only kept going under difficult circumstances, publishing outstanding examples of Big Data science and introducing innovations in the review process.

We have a Q&A with author Matthieu Foll from the WHO International Agency for Research on Cancer (IARC) on his new GigaScience paper presenting multi-omic data from rare lung neuroendocrine neoplasms and his experience having the precious Controlled Access data peer reviewed by named peer reviewers. As a journal focused on reproducibility of research GigaScience has a strict open-science policy, meaning

GigaScience has spawned a new smaller and more agile sibling: GigaByte, and is the first journal to come from our new GigaScience Press.

We have a new preprint out. This is a short post to describe our findings and highlight some of the software I developed for analysing cell migration and cell shape data.