A while back I made this little Automator script to convert Microsoft Word doc and docx files to PDF. It’s useful for when you are sent a bunch of Word files for committee work. Opening PDFs in Preview is nice and hassle-free. Struggling with Word is not. It’s not my own work, I just put it together after googling around a bit. I’ll put it here for anyone to use. To get it working: Open Automator.
I was searching for the excitation and emission spectra for mNeonGreen. I was able to find an image, but no values for the spectra.
I put a recent code snippet put up on the IgorExchange. It’s a simple procedure for averaging a set of 1D waves and putting the results in a new wave. The difference between this code and Average Waves.ipf (which ships with Igor) is that this function takes the average of all points in the wave and places this single value in a new wave. You can specify whether the mean or median is used for the average.
This is a long post about Journal Impact Factors. Thanks to Stephen Curry for encouraging me to post this.
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 that are resubmitted. This makes comparisons difficult.
My interest in publication lag times continues. Previous posts have looked at how long it takes my lab to publish our work, how often trainees publish and I also looked at very long lag times at Oncogene. I recently read a blog post on automated calculation of publication lag times for Bioinformatics journals. I thought it would be great to do this for Cell Biology journals too.
In this post I’ll describe a computational method for splitting two sides of a cell biological structure. It’s a simple method that relies on principal component analysis , otherwise known as PCA.
Having recently got my head around violin plots, I thought I would explain what they are and why you might want to use them. There are several options when it comes to plotting summary data. I list them here in order of granularity, before describing violin plots and how to plot them in some detail. Bar chart This is the mainstay of most papers in my field.
I realised recently that I’ve maintained a consistent iTunes library for ~10 years. For most of that time I’ve been listening exclusively to iTunes, rather than to music in other formats.
A bit of navel gazing for this post. Since moving the blog to wordpress.com in the summer, it recently accrued 5000 views. Time to analyse what people are reading… The most popular post on the blog (by a long way) is “Strange Things“, a post about the eLife impact factor (2824 views). The next most popular is a post about a Twitter H-index, with 498 views.
