In the UK there is an advertising disclaimer that “the value of your investments may go down as well as up.” Since papers are our main commodity in science and citations are something of a return, surely the “value” of a published paper only ever increases over time. Doesn’t it? I think this is true when citations to a paper are tracked at a conventional database (Web of Science for example). Citations are added and very rarely taken away.

To validate our analyses, I’ve been using randomisation to show that the results we see would not arise due to chance. For example, the location of pixels in an image can be randomised and the analysis rerun to see if – for example – there is still colocalisation. A recent task meant randomising live cell movies in the time dimension , where two channels were being correlated with one another.

We have a new paper out! You can access it here. The people This paper really was a team effort. Faye Nixon and Tom Honnor are joint-first authors. Faye did most of the experimental work in the final months of her PhD and Tom came up with the idea for the mathematical modelling and helped to rewrite our analysis method in R. Other people helped in lots of ways.

I’ve generated a lot of code for IgorPro. Keeping track of it all has got easier since I started using GitHub – even so – I have found myself writing something only to discover that I had previously written the same thing. I was thinking that it would be good to make a list of all functions that I’ve written to locate long lost functions.

Caution: this post is for nerds only. I watched this numberphile video last night and was fascinated by the point pattern that was created in it. I thought I would quickly program my own version to recreate it and then look at patterns made by more points. I didn’t realise until afterwards that there is actually a web version of the program used in the video here. It is a bit limited though so my code was still worthwhile.

Previously I wrote about our move to electronic lab notebooks (ELNs). This post contains the technical details to understand how it works for us. You can even replicate our setup if you want to take the plunge. Why go electronic? Many reasons: I wanted to be able to quickly find information in our lab books.

We finally took the plunge and adopted electronic lab notebook (ELNs) for the lab. This short post describes our choice of software. I will write another post about how it’s going, how I set it up and other technical details. tl;dr we are using WordPress as our ELN. First, so you can understand my wishlist of requirements for the perfect ELN. Easy-to-use. Allow adding pictures and notes easily.

I recently asked on Twitter for any recommendations for software to organise my PDFs. I got several replies, but nothing really fitted the bill. This is a brief summary. My situation I have quite a lot of books, textbooks, cheat sheets, manuals, protocols etc. in PDF format and I need a way to organise them.

BBC 6Music recently went back in time to 1994. This made me wonder what albums released that year were my favourites. As previously described on this blog, I have this information readily available. So I quickly crunched the numbers. I focused on full-length albums and, using play density (sum of all plays divided by number of album tracks) as a metric, I plotted out the Top 20.

Lab meetings: love them or loathe them, they’re an important part of lab-life. There’s many different formats and ways to do a lab meeting. Sometimes it feels like we’ve tried them all! I’m going to describe our current format and then discuss some other things to try. Our current lab meeting format is: Weekly. For one hour (Wednesdays at 9am) One person each week talks about their progress. It rotates around.

A large amount of time doing data analysis is the process of cleaning, importing, reorganising and generally not actually analysing data but getting it ready to analyse. I’ve been trying to get over the idea to non-coders in the group that strict naming conventions (for example) are important and very helpful to the poor person who has to deal with the data.