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: Programming I make no claim to be a computer wizard. My first taste of programming was the same as anyone who went to school in the UK in the 1980s: BBC Basic.

The future of cell biology, even for small labs, is quantitative and computational. What does this mean and what should it look like? My group is not there yet, but in this post I’ll describe where we are heading. The graphic below shows my current view of the ideal workflow for my lab.

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.

I needed to generate a uniform random distribution of points inside a circle and, later, a sphere. This is part of a bigger project, but the code to do this is kind of interesting. There were no solutions available for IgorPro, but stackexchange had plenty of examples in python and mathematica. There are many ways to do this.

An occasional series in esoteric programming issues. As part of a larger analysis project I needed to implement a short program to determine the closest distance of two line segments in 3D space. This will be used to sort out which segments to compare… like I say, part of a bigger project. The best method to do this is to find the closest distance one segment is to the other when the other one is represented as an infinite line.

Top Trumps is a card game for children. The mind can wander when playing such games with kids… typically, I start thinking: what is the best strategy for this game? But also, as the game drags on: what is the quickest way to lose? Since Top Trumps is based on numerical values with simple outcomes, it seemed straightforward to analyse the cards and to simulate different scenarios to look at these questions.

Fans of probability love random processes. And lotteries are a great example of random number generation. The UK National Lottery ran in one format from 19/11/1994 until 7/10/2015. I was talking to somebody who had played the same set of numbers in all of these lottery draws and I wondered what the net gain or loss has been for them over this period.

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.

Previously, I wrote a post with tips for new PIs on lab organisation. Since that time, I’ve started using Trello to organise operations in my lab. Trello is basically a way to track the progress of projects. Collaborative working is built-in. A friend had begun using Trello as she got involved in building an app. It seems that Trello is popular among teams working to develop software.

For the past 3.5 yrs I’ve been using Unison to sync files between 3 macs. It works great. In fact, since I installed and set up my profiles for syncing, I’ve not needed to change a thing. Until yesterday. I upgraded to El Capitan on each of the 3 macs. I went to run Unison to sync the days work and – an error. -bash: unison: command not found Oh dear. I looked in the search path and couldn’t find Unison.