With the fervour of someone with an n = 1 positive experience, I thought I’d write about what I learned from a recent writing retreat. My University organises one-day events to encourage writing. They’re on-campus, in the neutral territory of the Library, so perhaps calling them “writing retreats” is a little far-fetched. Nonetheless, the idea is to provide a time and space for people to achieve some writing.

One of the joys of posting a preprint is seeing that people are viewing, downloading and (hopefully) reading your paper. On bioRxiv you can check out the statistics for your paper in the metrics tab. We posted a preprint recently and it clocked up over 1,000 views in the first day or so. This made me wonder: is that a lot of views or not? How does it compare to other preprints in our category?

Previously, I took advantage of a dataset that linked preprints to their published counterparts to look at the fraction of papers in a journal that are preprinted. This linkage can be used to answer other interesting questions. Such as: when do authors preprint their papers relative to submission? And does this differ by journal? There’s a bit of preamble. If you just want to know the answer, click here.

Hot on the heals of the post on how to downsize microscopy movie files, let’s look at ways to shrink the size of a PDF file. There’s several ways to tackle this – suggestions came from this thread on Mastodon. Scenario: you have created a preprint/manuscript/proposal in PDF format.

Answering the question of what fraction of a journal’s papers were previously available as a preprint is quite difficult to do. The tricky part is matching preprints (from a number of different servers) with the published output from a journal.

Bands have been known to declare “No Synths!” on their albums. This statement was a badge of pride indicating that the artists hadn’t used any modern trickery in their recordings. Today, the growing use of artificial intelligence (AI) and large language models (LLMs) in science has created a similar scenario. Advocates argue that these tools improve every aspect of science, including the publication process.

In a previous post, I looked at how Google Scholar ranks co-authors. While I had the data available I wondered whether paper authorship could be used in other ways. A few months back, John Cook posted about using Jaccard index and jazz albums. The idea is to look at the players on two jazz albums and examine the overlap.

We have a new paper out describing how vesicles move inside cells. The paper in a nutshell In science-speak We analysed how small vesicles are transported in cells. In contrast to large vesicles and organelles, which move using motors inside cells, our analysis revealed that passive diffusion is the main mode of small vesicle transport. In normal language Inside cells, molecules are moved in tiny transport packets called vesicles.

On a scientist’s Google Scholar page, there is a list of co-authors in the sidebar. I’ve often wondered how Google determines in what order these co-authors appear. The list of co-authors on a primary author’s page is not exhaustive. It only lists co-authors who also have a Google Scholar profile. They also have to be suggested to the primary author and they need to accept the co-author to list them on the page.

When preparing images for publication, it is good practice to check how accessible they are for colour blind people. Using a simple bit of code, it is possible to check an image – or a whole figure – in ImageJ for accessibility. For example, Figure 1 from our recent paper. Originally looked like this: Using the script we can see how it appears to people with different types of colour blindness.