Yesterday I tried a gedankenexperiment via Twitter, and asked: If you could visualise a protein relative to an intracellular structure/organelle at ~5 nm resolution, which one would you pick and why? https://twitter.com/clathrin/status/707949738323218432 I got some interesting replies: Myosin Va and cargo on actin filaments in melanocytes – Cleidson Alves @cleidson_alves COPII components relative to ER and Golgi for export of

Every Song Ever: Twenty Ways to Listen in an Age of Musical Plenty Ben Ratliff (Farrar, Straus and Giroux) {.alignleft .size-medium .wp-image-756 loading=“lazy” decoding=“async” attachment-id=“756” permalink=“https://quantixed.org/41lkbxvsugl- sx329_bo1204203200 /” orig-file=“https://i0.wp.com/quantixed.org/wp-content/uploads/2016/03/41lkbxvsugl- sx329_bo1204203200 .jpg?fit=331%2C499&ssl=1”

The end of the month sees the Coventry Half Marathon. I looked at what constitutes a good time over this course, based on 2015 results. I thought I’d post this here in case any one is interested.

I was interested in the analysis by Frontiers on the lack of a correlation between the rejection rate of a journal and the “impact” (as measured by the JIF). There’s a nice follow here at Science Open.

University of Warwick is a popular conference destination, with thousands of visitors per year. Next time you visit and stay on campus, why not bring your running shoes and try out these routes?

There have been calls for journals to publish the distribution of citations to the papers they publish (1 2 3). The idea is to turn the focus away from just one number – the Journal Impact Factor (JIF) – and to look at all the data. Some journals have responded by publishing the data that underlie the JIF (EMBO J, Peer J, Royal Soc, Nature Chem). It would be great if more journals did this.

A few days ago, Retraction Watch published the top ten most-cited retracted papers. I saw this post with a bar chart to visualise these citations. It didn’t quite capture what the effect (if any) a retraction has on citations. I thought I’d quickly plot this out for the number one article on the list.

This year #paperOTD (or paper of the day for any readers not on Twitter) did not go well for me. I’ve been busy with lots of things and I’m now reviewing more grants than last year because I am doing more committee work. This means I am finding less time to read one paper per day. Nonetheless I will round up the stats for this year.

I read this article on the BBC recently about alcohol consumption in the UK. In passing it mentions how many people in the UK are teetotal. I found the number reported – 21% – unbelievable so I checked out the source for the numbers.

bioRxiv, the preprint server for biology, recently turned 2 years old. This seems a good point to take a look at how bioRxiv has developed over this time and to discuss any concerns sceptical people may have about using the service.

Our recent paper on “the mesh” in kinetochore fibres (K-fibres) of the mitotic spindle was our first adventure in 3D electron microscopy. This post is about some of the new data analysis challenges that were thrown up by this study. I promised a more technical post about this paper and here it is, better late than never.