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Ewan Birney Profile picture
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17 Sep, 4 tweets, 1 min read
I think the imperial weights thing in the UK is silly (deeply silly) but I do think there was more method in "12" units (and for that matter, 60). 12 is a nice number for division (halves, thirds, quarters, sixths) and then the next nice number for division is 60 (fifths).
Of course the pounds to stone (14!) and then madness of Guineas (I still don't really understand) doesn't fit this. On historical numerology, I was reminded of the arcane voting system for the Dodge in Venice that involves 11, 13s and 17s as supposed "hard to game" prime numbers
As well as the measuring unit changing depending on what you were measuring (this is another moment of deep madness) I think this use of effectively base 12 might be more about early medieaval maths and plenty of mental arithmetic.
...none of this historic perspective though means one should bring this back in for legal weights and measures....

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More from @ewanbirney

Ewan Birney Profile picture
19 Sep
In general the response I think to the announcement of a polygenic-risk-score informed embryo selection has been right - one where the science is wrong, the clinical harm/benefit therefore also wrong, and one where ethical/societal considerations have to be folded in. However...
There are some people who say "but even if this is wrong now, it might not in the future" (true) and also "if genetics works, then this should work" often with some handwaving towards farm animal genetics/breeding/selection. In this twitter thread I'd like to tackle this.
(Context: I am a geneticist/genomicist. My two favourite organisms to study humans and Japanese rice paddy fish. I'm on the experiments/practical data science side, but have a pretty good understanding of the theory/stats side, partly because I've coded it myself/in my group)
Read 23 tweets
Ewan Birney Profile picture
18 Sep
So depressing rereading this thread of the first embryo selection by broad genomic profiling from healthy donors in the US
A reminder; in the UK this process would clearly fall under HFEA, and applications to do this would almost certainly be rejected on ethical / societal grounds, on clinical harm to benefit and underlying scientific validity
I’m very positive about the use of genomics in healthcare - many diverse uses and its growing - but I am firmly against this use on ethics, clinical (I’m not an expert) and science (I am an expert). Blogged on this in 2019 ewanbirney.com/2019/05/why-em…
Read 4 tweets
Ewan Birney Profile picture
17 Sep
After a great workshop in Paris (and hopefully, testing being ok, I will be returning next week) I've been thinking about my travel in the new normal, thinking about green (lowering carbon)
This has been informed by conversations with colleagues such as @embl's green officer, @BrenRouseHD, faculty colleagues such as @Alexbateman1, @PaulFlicek and Deltev Arendt (many thanks); these are currently my thoughts on this (insight from colleagues; missteps from me!)
First off pre-pandmic science travel was useful but often mad; flying for single meetings (sometimes in windowless rooms) with fast turn arounds. Not only was it carbon expensive but it was also bad for family life and just plain health.
Read 16 tweets
Ewan Birney Profile picture
10 Sep
As we enter yet another period of COVID uncertainity over outcomes (due mainly to human behaviour - what does "baseline/new normal" contacts look like in an European Autumn/Winter) a reminder about models. There are at least 3 different types; explanatory, forecast and scenario.
Explanatory - usually retrospective data to fit an understanding of the world (say infection->hospitalistion/not->death/discharge) for time series. Examples: excess deaths attributable to COVID, vaccine efficacy models and biological properties of variants.
Forecast - fit an up to date time series to understand outcomes in the near future, sometimes just to understand "now" (hence "nowcasting"). Examples: R rate and near time extrapolation; hospitalisation capacity near term management (often not public).
Read 8 tweets
Ewan Birney Profile picture
9 Sep
My annual reminder; if you propose doing large scale data gathering and analysis, just a *one sentence* power calculation, or "we have confidence this approach can provide robust results due to similar work of XXX in system YYY with similar sample sizes".
Why is this important in a grant? As a reviewer wont be able to fully check your power calculation (usually) but I do want to see that you are honest with *yourself* about whether the stats are going to work out. Too few samples, expected weak effects => it's never going to work
If your power calculation (which will always be pulling numbers out of the air for effect size etc; such is science) says its very unlikely you will find a credible result then... you need to reset your goals.
Read 6 tweets
Ewan Birney Profile picture
5 Sep
COVID thoughts from London, after a yesterday's day of slow cricket; TL;DR - the pandemic is reasonably predictable except for human behaviour on contacts; Europe will be likely navigating a complex winter; US (still) needs to vaccinate; The world needs more vaccines.
Context: I am an expert in genetics and computational biology. I know experts in viral genomics, infectious epidemiology, immunology and clinical trials. I have some COIs - I am a longestablished consultant to Oxford Nanopore and was on the Ox/Az vaccine trial.
Reminder: SARS-CoV-2 is a respiratory human virus where a subset of people infected get a horrible disease, COVID, often leading to death. Left unchecked many people would die and healthcare systems would have overflowed.
Read 25 tweets

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