Author Archives: Charlie Clark

LOADING: an art and science collaborative project

For the past few months, OPIGlets Gemma, Charlie and Alexi have been engaged in a collaboration between scientists from Oxford and artists connected to Central St Martins art college in London. This culminated in February with the publication of a zine detailing our work, and a final symposium where we presented our projects to the wider community.

This collaboration was led by organisers Barney Hill and Nina Gonzalez-Park and comprised a series of workshops in various locations across Oxford and London, where the focus was to discuss commonalities between contemporary artistic and scientific research and the concept of transdisciplinary work. Additionally, scientists and artists were paired up to explore shared interests, with the goal of creating a final piece to exhibit.

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Walk through a cell

In 2022, Maritan et al. released the first ever macromolecular model of an entire cell. The cell in question is a bacterial cell from the genus Mycoplasma. If you’re a biologist, you likely know Mycoplasma as a common cell culture contaminant.

Now, through the work of app developer Timothy Davison, you can interactively explore this cell model from the comfort of your iPhone or Apple Vision Pro. Here are three reasons why I like CellWalk:

1. It’s pretty

The visuals of CellWalk are striking. The app offers a rich depiction of the cell, allowing the user to zoom from the whole cell to individual atoms. I spent a while clicking through each protein I could see to see if I could guess what it was or what it did. Zooming out, CellWalk offers a beautiful tripartite cross section of the cell, showing first the lipid membrane, then a colourful jumble-bag of all its cellular proteins, and then finally the spaghetti-like polynucleic acids.

Tripartite cross section of a Mycoplasma cell. Screengrab taken from the CellWalk app on my phone.
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Quickly (and lazily) scale your data processing in Python

Do you use pandas for your data processing/wrangling? If you do, and your code involves any data-heavy steps such as data generation, exploding operations, featurization, etc, then it can quickly become inconvenient to test your code.

  • Inconvenient compute times (>tens of minutes). Perhaps fine for a one-off, but over repeated test iterations your efficiency and focus will take a hit.
  • Inconvenient memory usage. Perhaps your dataset is too large for memory, or loads in but then causes an OOM error during a mid-operation memory spike.
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