I really loathe reviewing for GlamMagz for two main reasons. For one, it’s hard to remain neutral: publication of a paper in my field in such a journal is beneficial both for the field and for the young people who are authors on this paper. Second, the demands of some of my colleagues so often make my blood boil. At that point I’m very happy these reviews are anonymous and I really don’t want to know the names of these colleagues.

Open Science has emerged into the mainstream, primarily due to concerted efforts from various individuals, institutions, and initiatives. This small, focused gathering brought together several of those community leaders.  The purpose of the meeting was to define common goals, discuss common challenges, and coordinate on common efforts.

Our most recent manuscript was almost ready for submission. We were planning to send it to an open access journal. It was then that I had the thought: how many papers in the reference list are freely available? It somehow didn’t make much sense to point readers towards papers that they might not be able to access. So, I wondered if there was a quick way to determine how papers in my reference list were open access.

Following on from the last post about publication lag times at cell biology journals, I went ahead and crunched the numbers for all journals in PubMed for one year (2013). Before we dive into the numbers, a couple of points about this kind of information. Some journals “reset the clock” on the received date with manuscripts that are resubmitted. This makes comparisons difficult.

My interest in publication lag times continues. Previous posts have looked at how long it takes my lab to publish our work, how often trainees publish and I also looked at very long lag times at Oncogene. I recently read a blog post on automated calculation of publication lag times for Bioinformatics journals. I thought it would be great to do this for Cell Biology journals too.

I thought I’d share this piece of analysis looking at productivity of people in the lab. Here, productivity means publishing papers. This is unfortunate since some people in my lab have made some great contributions to other peoples’ projects or have generally got something going, but these haven’t necessarily transferred into print. Also, the projects people have been involved in have varied in toughness.

We have a new paper out! You can access it here. The work was mainly done by Cristina Gutiérrez Caballero, a post-doc in the lab. We had some help from Selena Burgess and Richard Bayliss at the University of Leicester, with whom we have an ongoing collaboration. The paper in a nutshell We found that TACC3 binds the plus-ends of microtubules via an interaction with ch-TOG. So TACC3 is a +TIP.

Having recently got my head around violin plots, I thought I would explain what they are and why you might want to use them. There are several options when it comes to plotting summary data. I list them here in order of granularity, before describing violin plots and how to plot them in some detail.

I was talking to a speaker visiting our department recently. While discussing his postdoc work from years ago, he told me about the identification of the sperm factor that causes calcium oscillations in the egg at fertilisation. It was an interesting tale because the group who eventually identified the factor – now widely accepted as PLCzeta – had earlier misidentified the factor, naming it oscillin.

[Guest post from Lisa O’Sullivan, Director, Center for the History of Medicine and Public Health]{style=“font-family: "arial" , "sans-serif"; mso-fareast-font-family: "Times New Roman"; mso-fareast-language: EN-GB;”} [By now it’s axiomatic that the digital world poses new opportunities and challenges for researchers, libraries, educational institutions, and publishers, which must be engaged with digital formats in a sustained and