This post follows on from “Getting Started“. In the lab we use IgorPRO for pretty much everything. We have many analysis routines that run in Igor, we have scripts for processing microscope metadata etc, and we use it for generating all figures for our papers. Even so, people in the lab engage with it to varying extents. The main battle is that the use of Excel is pretty ubiquitous.

More on the theme of “The Digital Cell“: using quantitative, computational approaches in cell biology. So you want to get started? Well, the short version of this post is: Find something that you need to automate and get going! Programming http://www.instruction-manuals.co.uk/imageIM/four/seven/bbc.gif I make no claim to be a computer wizard.

If you are a cell biologist, you will have noticed the change in emphasis in our field. At one time, cell biology papers were – in the main – qualitative . Micrographs of “representative cells”, western blots of a “typical experiment”… This descriptive style gave way to more quantitative approaches, converting observations into numbers that could be objectively assessed.

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.

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.

In the lab we have been doing quite a bit of analysis of cell migration in 2D. Typically RPE1 cells migrating on fibronectin-coated glass. There are quite a few tools out there to track cell movements and to analyse their migration. Naturally, none of these did quite what we wanted and none fitted nicely into our analysis workflow. This meant writing something from scratch in IgorPro. You can access the code from my GitHub pages.

A couple of years ago, a colleague sent me this picture* to say “who put J Cell Biol on a diet?”. I joked that maybe they publish too many autophagy papers and didn’t think much more of it. Recently, Ron Vale put up this very interesting piece on bioRxiv discussing what it takes to publish a paper in the field of cell biology these days. In the main, he questions whether this is now out of reach of many trainees in our labs.

We have a new paper out! You can access it here. Title of the paper: The mesh is a network of microtubule connectors that stabilizes individual kinetochore fibers of the mitotic spindle What’s it about? When a cell divides, the two new cells need to get the right number of chromosomes. If this process goes wrong, it is a disaster which may lead to disease e.g. cancer.

I was searching for the excitation and emission spectra for mNeonGreen. I was able to find an image, but no values for the spectra.