The Digital Cell

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. […]

Adventures in code II

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 […]

Adventures in code

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 […]

The Great Curve: Citation distributions

This post follows on from a previous post on citation distributions and the wrongness of Impact Factor. Stephen Curry had previously made the call that journals should “show us the data” that underlie the much-maligned Journal Impact Factor (JIF). However, this call made me wonder what “showing us the data” would look like and how journals might […]

Wrong Number: A closer look at Impact Factors

This is a long post about Journal Impact Factors. Thanks to Stephen Curry for encouraging me to post this. tl;dr — I really liked this recent tweet from Stat Fact It’s a great illustration of why reporting means for skewed distributions is a bad idea. And this brings us quickly to Thomson-Reuters’ Journal Impact Factor […]