Beyond the thousands of deaths and the millions of infected people, the COVID-19 pandemic has quickly transformed Western society. This virus has provoked the confinement of millions of people in their houses, the closure of bars, restaurants, and pubs, schools, museums, and theatres. However, for this post, I will focus on another side effect of the pandemic: the spread of canards, which flow even faster than the virus itself.
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Converting Miles to Kilometres – An inefficient but neat method
Picture this: You’re a zealous acolyte of the metric system, with a rare affliction that makes multiplying decimal numbers impossible. You’re on holiday in the UK, where road signs give distances in miles. Heathens! How can you efficiently estimate the number of kilometres without multiplying by approximately 1.60934?
Continue readingCoronavirus
A zoonosis is an infectious disease that has jumped from a non-human animal to humans.
The coronavirus disease 2019 (COVID-19) is one such zoonosis, and is caused by severe acute respiratory syndrome coronavirus 2 (SARS coronavirus 2, SARS-CoV-2, or 2019-nCoV). This is very similar to the SARS virus that emerged in 2003. Its recent emergence has resulted in a WHO-declared public health emergency of international concern.
Continue readingTransforming Parliament – Training and deploying speech generation transformers for parliamentary speakers
Introduction
I recently wanted to explore areas of machine learning that I do not usually interact with as part of my DPhil research on antibody drug discovery. This post explores how to train and deploy a speech generation model for parliamentary speeches in the style of Jeremy Corbyn and Boris Johnson. You can play around with the resulting model at https://con-schneider.github.io/theytalktoyou.html.
Continue readingThings I’ve Learned from Hosting Speaker Events
For the past couple of years I’ve been involved in running the Oxford University Scientific Society. We host weekly talks in Oxford during the Undergraduate Term, inviting speakers from all scientific disciplines to come and discuss their field with our members. Here are four important lessons I’ve learned from being involved!
Prof. Charlotte Deane on the World Service
Prof. Charlotte Deane, the new Deputy Executive Chair of the EPSRC, Deputy Head of Division of MPLS, and Head of the Oxford Protein Informatics Group, was interviewed by BBC World Service’s programme “Tech Tent”, about the role of AI in drug discovery; jump to about 13:30 to hear Charlotte, and the segment on AI in healthcare starts at 9:45:
Bringing practical bioinformatics to high school classrooms
Back in July a litter of OPIGlets went rooting for interesting science at ISMB/ECCB 2019 in Basel, Switzerland. When not presenting, working on my sunburn, or paying nine Francs for a beer, I made a point to attend talks outside my usual bubble of machine learning and drug discovery. In particular, I spent the latter half of the conference in the Education track, and am very glad I did. I love teaching, and am always excited to learn from more experienced educators and trainers. Today I’m going to talk about a fantastic presentation by Stevie Bain from the University of Edinburgh about introducing practical bioinformatics to high school biology classrooms through the 4273pi project.
Continue readingGene-Edited Crops
Oxford Maths Festival ‘19
The Oxford Maths Festival returned this year and it was tons of fun, at least for this volunteer! I failed to take pictures, but a few opiglets were involved: Flo and company took their VR work for the Ashmolean Dimensions exhibit and demonstrated it at Templars Square, and Conor did a spectacular job pretending to be a police constable for the maths escape room.
Last year Mark blogged about how we demonstrated the German Tank Problem at the festival. I thought this time round I’d share another of the Mathematical Mayhem activities: a game illustrating biased sampling.
Continue readingWhat is the hydrophobic-polar (HP) model?
Proteins are fascinating. They are ubiquitous in living organisms, carrying out all kinds of functions: from structural support to unbelievably powerful catalysis. And yet, despite their ubiquity, we are still bemused by their functioning, not to mention by how they came to be. As computational scientists, our research at OPIG is mostly about modelling proteins in different forms. We are a very heterogeneous group that leverages approaches of diverse scale: from modelling proteins as nodes in a complex interaction network, to full atomistic models that help us understand how they behave.
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