Category Archives: Notes

How ChatGPT changed my writing as an ESL speaker

It’s not always easy to live in an Anglophone scientific world when English isn’t your first language. When careers are built upon the ability to communicate ideas clearly and eloquently, struggling to find the right words can be a real hindrance to explain your science in a way that is taken seriously. Contrary to popular belief, it’s not something you can simply “work” on. Often, it doesn’t matter how many books you’ve read, how many years of education you have, or how articulate you are in your original language — your brain will refuse to summon the right expression, or get stuck in a construction that a native speaker would never use. Struggling with a second language is very much a biological phenomenon.

The standard recommendation for ESL (English as a Second Language) speakers has long been to ask a native colleague to read through any text that needs to be published or submitted somewhere (such as an article or a grant application). Well-intentioned as this advice may be, there are multiple problems with it. Lingua franca or not, only 15% of the world population speaks English, of which only 5% are native speakers — meaning that for most scientists not working in Anglophone countries, the option is rarely available. Even when available, it is unreasonable to expect these colleagues to add charitable proof-reading to their workload simply because they happened to be born speaking a different language. But, most importantly, I have always felt — and I want to emphasize that I truly believe most people who issue this kind of advice to be well-intentioned — that the underliying message sounds too much like “you need vetting by a member of our select linguistic club if you want your ideas to be taken seriously“.

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Supercharge Your Literature Review With These Tools

When starting a new project, conducting a literature review of the field can be one of the most daunting prospects. Not only do you need to get through a mountain of research papers, you also need to work out which mountain of papers to get through. You don’t want to start a project only to realise a few weeks (or months!) in that you missed a key paper which would have completely changed the course of your research. Luckily, there are now several handy tools which can help speed up this process.

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Benchmarks in De Novo Drug Design

I recently came across a review of “De novo molecular drug design benchmarking” by Lauren L. Grant and Clarissa S. Sit where they highlighted the recently proposed benchmarking methods including Fréchet ChemNet Distance [1], GuacaMol [2], and Molecular Sets (MOSES) [3] together with its current and future potential applications as well as the steps moving forward in terms of validation of benchmarking methods [4].

From this review, I particularly wanted to note about the issues with current benchmarking methods and the points we should be aware of when using these methods to benchmark our own de novo molecular design methods. Goal-directed models are referring to de novo molecular design methods optimizing for a particular scoring function [2].

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You’re getting on my biscuits

Jaffa cakes are God’s own snacks and I will brook no opposition. I don’t mind if they’re McVitie’s brand Jaffa cakes, or Pim’s, the suspicious European variety. Even Sainsbury’s Basics Jaffa cakes float my balloon. Take a soft sponge base, slap some jam and chocolate on that puppy, and you’re golden.

But if you describe your love of these glorious creations, the conversation takes a familiar turn. Are they cakes or are they biscuits? it goes. HMRC tried to classify them as cakes – or was it biscuits? Something like that. It had to do with VAT…

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Common denominators between a PhD and an Oxford ball

One of the things I love about Oxford is the way it pushes you to become a well-rounded person. It does so by means of a wealth of talks and lectures, and also through the college system that encourages meeting people from different disciplines, but above all through the strong culture of student projects. This place will encourage you, perhaps even push you, to take part in fantastic projects that will make the already very demanding workload even worse… but also teach you incredible skills and get you to work with wonderful, inspiring people.

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A new way of eating too much

Fresh off the pages of Therapeutic Advances in Endocrinology and Metabolism comes a warning no self-respecting sweet tooth should ignore.

“Liquorice is not just a candy,” write a team of ten from Chicago. “Life-threatening complications can occur with excess use.” Hold on to your teabags. Liquorice – the Marmite of sweets – is about to become a lot more sinister.

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Oh lord, they comin’ – a diversity of units

For scientists, units are like money: a few people obsess about them, but the less you have to think about units, the better. And, like switching a bank account, changing your units is usually tiresome and complicated for little real advantage. But spare a thought for the many units that have been lost to the inexorable march of scientific advance, and for the few that are still in regular use.

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Why you should care about type hints in Python

Duck typing is great. Knowing that as long as my object does what the function expects it to, I can pass it to the function and get my results without having to worry about exactly what else my object might do. Coming from statically-typed languages such as Java and C++, this is incredibly liberating, and makes it easy to rapidly prototype complex and expressive code without worrying about checking types everywhere. This expressiveness, however, comes with a cost: type errors are only caught at runtime, and can be hard to debug if the original author didn’t document what that one variable in that one function signature is expected to look like.

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A gentle primer on quantum annealing

If you have done any computational work, you must have spent some time waiting for your program to run. As an undergraduate, I expected computational biology to be all fun and games: idyllic hours passing time while the computer works hard to deliver results… well, very different from the more typical frenetically staring at the computer, wishing the program would run faster. But there is more — there are some problems that are so intrinsically expensive that, even if you had access to all the computers on Earth, it would take more than your lifetime to solve a slightly non-trivial case of them. Some examples are full configuration interaction calculations in quantum chemistry, factorisation of prime numbers, optimal planning, and a long, long, etcetera. Continue reading

A blog post about a blog

I thought I would make this blog post very meta by referring to another blog, written by Lior Pachter, which I think has something for many of us in it: http://liorpachter.wordpress.com (networks people, there’s a pretty scathing take-down of a quite well cited 2013 paper as one of the last posts – there seem to be a couple of posts labelled “network nonsense”!)

In particular I refer you to the list, that Lior Pachter has curated, which includes all variations of *-seq. You’ll see that practically all sequencing protocols take on this nomenclature of catchy descriptor + seq.

You will have heard mention of Ig-seq in talks by antibody people (with all Ig-seq experiments being curated in OAS by Alex). Ig-seq comes under the “Phenotyping” section of Lior’s list.

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