Towards the end of 2015, I started distance running. I thought it’d be fun to look at the frequency of my runs over the course of 2016. Most of my runs were recorded with a GPS watch. I log my cycling data using Rubitrack, so I just added my running data to this. This software is great but to do any serious number crunching, other software is needed.
We have some macros for ImageJ/FIJI for making figures and blind analysis which could be useful to others. I made an ImageJ Update Site so that the latest versions can be pushed out to the people in the lab, but this also gives the opportunity to share our code with the world. Feel free to add the quantixed ImageJ update site to your ImageJ or FIJI installation. Details of how to do that are here.
I’ve returned from the American Society for Cell Biology 2016 meeting in San Francisco. Despite being a cell biologist and people from my lab attending this meeting numerous times, this was my first ASCB meeting.
This is part-tip, part-adventures in code. I found out recently that it is possible to comment out multiple lines of code in Igor and thought I’d put this tip up here.
I don’t often write about music at quantixed but I recently caught Survivor’s “Eye of The Tiger” on the radio and thought it deserved a quick post. Surely everyone knows this song: a kind of catchall motivational tune.
Molecular Biology of The Cell , the official journal of the American Society for Cell Biology, recently joined a number of other periodicals in issuing guidelines for manuscripts, concerning statistics and reproducibility.
This is a quick post about the punch card feature on GitHub. This is available from Graphs within each repo and is also directly accessible via the API. I was looking at the punch card for two of my projects: one is work related and the other, more of a kind of hobby. The punch cards were different (the work one had way more commits, 99, than the hobby, 22). There was an interesting pattern to them. Here they are overlaid.
A couple of recent projects have meant that I had to get to grips more seriously with R and with MATLAB . Regular readers will know that I am a die-hard IgorPro user. Trying to tackle a new IDE is a frustrating experience, as anyone who has tried to speak a foreign language will know. The speed with which you can do stuff (or get your point across) is very slow.
Ten years ago today I became a PI. Well, that’s not quite true. On that day, I took up my appointment as a Lecturer at University of Liverpool, but technically I was not a PI. I had no lab space (it was under construction), I had no people, and I also had no money for research. I arrived for work.
I’m currently writing two manuscripts that each have a substantial data modelling component. Some of our previous papers have included computer code, but it was straightforward enough to have the code as a supplementary file or in a GitHub repo and leave it at that. Now with more substantial computation in the manuscript, I was wondering how best to describe it. How much detail is required?
