Tracking changes in Microsoft Word is easy – we just click the ‘Track Changes’ button. It requires a little more work in LaTeX but here is a quick guide to doing it as painlessly as possible!
First, we want our original document to be stored in a *.tex file in an Overleaf project (as shown below)
Continue readingPlants can be genetically engineered to express non-native proteins, for example, crops can be engineered to produce insect toxins in order to improve disease-resistance. However, I was not aware of their ability to express antibodies until, inspired by my expanding collection of house plants, I googled ‘plant immune systems’.
Plants don’t naturally produce antibodies – they do not possess an adaptive immune system or any circulating immune defence cells. Despite this, plants can be made to express and assemble full length antibody heavy chains and light chains. This was first published back in 1989, when Hiatt et al. [1] successfully introduced mouse immunoglobulin genes to tobacco plants and produced functional antibodies with reasonable efficiency. The excellent term ‘plantibody‘ was coined soon after, to refer to antibodies and fragments of antibodies produced by plants transformed with antibody-coding genes.
Continue readingPeople seem to have become obsessed with wordle, just like they became obsessed with sudoku. After my initial burst of “oh a new game!” had waned, I was left thinking “my time is precious and this is exactly what we have computers for”. With this in mind, below is my quick and dirty way of solving these. I’m sure the regexp gurus amongst you will have a more elegant solution.
Step 1: Make sure you’ve got /usr/share/dict/words installed. This is just a huge list of words in a specific language and for me, this required installing the British words list.
sudo apt-get install wbritish
Step 2: Go to wordle
Step 3: Pick a random 5-letter word as your starting point. This is where grep and /usr/share/dict/words comes in:
Continue readingFor my first blog post of the year, we’re talking about SLURM, everyone’s favorite job manager. If like me, you have the joy of running a literal boat-load of jobs with all kinds of parameters and command-line arguments you’ll know there are a few tips and tricks that make the process of managing these tasks and results as painless as possible. Now, I do expect most people reading this will already be aware of these tricks but for those who don’t, I hope this is helpful. After all, it’s impossible to know what you don’t know you need to know, you know? Any alternatives, improvements, or suggestions are welcome!
Job arrays are perfect for the times you want to run the same job several times with slight differences each time. Imagine you need to repeat a job 10 times with slightly different arguments with each run. Rather than submit 10 (slightly different) batch scripts you can submit 1 script with all the information needed to complete all 10 jobs.
Continue readingHappy 2022, Blopiggers!
My first post of the year is about another major change to the way the World Health Organisation will be assigning “International Non-proprietary Name”s (INNs) to antibody-based therapeutics. I haven’t seen this publicised widely, so I thought I’d share it here as it is an important consideration for anyone mining or exploiting this data.
In this blog post I describe the advantages of taking a stochastic view of chemical systems based on the work of D. T. Gillespie and subsequent publications. Gillespie presented his formalism for considering stochastic chemical kinetics, now referred to as the Gillespie Algorithm, in two papers published in 1976 and 1977 (Gillespie, D. T. J. Comp. Phys. 1976, Gillespie D. T. J. Phys. Chem. 1977) – if you want to see the full derivation for the Gillespie Algorithm along with many examples I recommend giving them both a read.
The essential question of chemical kinetics as stated by Gillespie is:
“If a fixed volume V contains a spatially uniform mixture of N chemical species which can inter-react through M specified chemical reaction channels, then given the numbers of molecules of each species present at some initial time, what will these molecular population levels be at any later time?”
Continue readingOne year on and the latest variant of SARS-CoV-2 spreading like wildfire, and OPIG found itself meeting virtually, again…
Perhaps the highlight of OPIGmas is the Secret Santa gift exchange (although some might beg to differ: in meat-space “beer” pong might compete for pole position). Alas, no crypto-currency was gifted this year…
Continue readingI was invited to speak at the Antibody Engineering and Therapeutics Conference (presenting mine and Matt’s recently published epitope profiling paper), in San Diego (December 12th – 16th). Unfortunately, the pandemic had other ideas so I decided not to travel but luckily the conference was hybrid.
The conference included 1 day of pre-conference workshops and 4 days of presentations from academic and industry, with livestreaming of the initial keynotes (including one from Charlotte). Remaining talks were recorded and made available after the conference. I’ve highlighted a few of my favourite talks and conference themes, with links to papers where available.
Naturally, a lot of the presented research related to covid-19. I was speaking in the ‘Antibody Repertoires and Covid-19’ session, where there were interesting presentations from Professor Eline Luning Prak from the University of Pennsylvania and Elaine Chen from Vanderbilt University analysing antibody responses in covid-recovered individuals, and comparing vaccine responses in covid-recovered vs covid-naiive individuals. Other talks around SARS-CoV-2 vaccines included Dr Laura Walker from Adimab/Adagio Therapeutics comparing BCR repertoire responses to different types of vaccinations, and the effect of using different booster types.
Continue readingFragment based drug discovery is a powerful technique for finding lead compounds for medicinal chemistry. Crystallographic fragment screening is particularly useful because it informs one not just about whether a fragment binds, but has the advantage of providing information on how it binds. This information allows for rational elaboration and merging of fragments.
However, this comes with a unique challenge: the confidence in the experimental readout, if and how a fragment binds, is tied to the quality of the crystallographic model that can be built. This intimately links crystallographic fragment screening to the general statistical idea of a “model”, and the statistical ideas of goodness of fit and overfitting.
Continue readingWhen developing your pipeline for processing, annotating and/or analyzing data, you will probably find yourself needing to continuously re-run it, as you play around with your code. This can become a problem when working with long pipelines, large datasets and cpu’s begging you not to run some pieces of code again.
Luckily, you are not the first one to have been annoyed by this and other related struggles. Some people were actually so annoyed that they created Snakemake. Snakemake can be used to create workflows and help solve problems, such as the one mentioned above. This is done using a Snakefile, which helps you split your pipeline into “rules”. To illustrate how this helps you create a better workflow, we will be looking at the example below.
Continue reading