I have written previously about Journal Impact Factors (here and here). The response to these articles has been great and earlier this year I was asked to write something about JIFs and citation distributions for one of my favourite journals. I agreed and set to work. Things started off so well. A title came straight to mind.

In her recent editorial on Sci-Hub (an initiative I support), editor-in-chief of Science Magazine Marcia McNutt wrote: The editorial is essentially trying to make the somewhat tenuous but not implausible case that using sci-hub may lead to subscription cancellations which, in turn, may lead to scholarly societies (like those of Dr. McNutts employer, AAAS) to miss revenue they need in order to pay for important services (such as paying

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

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.

In a big step forward for allowing proper credit to be provided to all of the awesome folks collecting and publishing data, the journal Global Ecology & Biogeography has just announced that they will start supporting an unlimited set of references to datasets used in a paper. These references will be included immediately following the traditional references section in both the html and pdf versions of the paper.

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.

For the past few years I’ve been involved in a collaboration to put together a broad-coverage life history database for mammals, reptiles, and birds. The project started because my collaborator, Nathan Myhrvold, and I both had projects we were interested in that involved comparing life history traits of reptiles, mammals, and birds, and only mammals had easily accessible life history databases with broad taxonomic coverage.

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.

Recently, over at the blog Ecological Rants the eminent ecologist Charles Krebs wrote a post about the ills of simplification in ecology. The post focuses specifically on how ecology has been ‘led astray’ by simplified models and lab studies. This has recently been picked up on Dynamic Ecology by Jeremy Fox who responded generally to the post but specifically to the affront to microcosms.