## The Digital Cell: Getting started with IgorPRO

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 […]

## The Digital Cell: Getting Started

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 I make no claim to be a computer wizard. My first taste of programming was the […]

## The Digital Cell: Workflow

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. The graphic is pretty self-explanatory, but […]

## 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. […]

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 […]

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 […]

## At a Crawl: Analysis of Cell Migration in IgorPro

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 […]

## 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 […]

## Waiting to happen II: Publication lag times

Following on from the last post about publication lag times at cell biology journals, I went ahead and crunched the numbers for all journals in PubMed for one year (2013). Before we dive into the numbers, a couple of points about this kind of information. Some journals “reset the clock” on the received date with manuscripts […]