A personal view point on the #AlphaFold announcement today from the @DeepMind and @emblebi team, part of @embl. TL;DR - I am *still* pinching myself about this.
When @demishassabis and the AlphaFold team first presented the results from CASP to me last November I genuinely almost fell off my chair. I think I swore quite a bit (in a British way) in amazement.
One of the reasons was I knew how rigorous CASP was - 20 years ago people published all sorts of "solving the folding problem" which then... didn't work beyond the training set. CASP cleverly used the fact that there are genuinely unknown structures each year solved by experiment
In CASP you have to put predictions into the competition of targets which are thought to be solved in the year; they cannot be in your training set. The presence of this well run, rigourous competition I think was one reason @DeepMind selected this problem
The other of course is that there is lots of complex data and knowledge - in evolution of protein sequences, in the fundamental chemistry of amino acids, in physical constraints to bring together.
Nevertheless this is clearly not "bring out your standard Inception Neural Network and define your output function" - it is complex to know what to represent to what type of deep learning scheme and how to integrate it. Respect to John Jumper and the AlphaFold team
That was amazing enough but then @demishassabis and the @DeepMind team had to work out the best way to get impact from this - at all sorts of levels - and wisely I think they realised it was best done openly, and if open, go "all in".
Huge *huge* credit here.
So - publish the method; open source the code; run the program on public data, and here it was great that the @DeepMind team approached us @emblebi to partner - in particular Sameer Velankar from @PDBeurope
As @demishassabis has said this is a sort of amplification cycle of the open (experimental) data present in @PDBeurope and @uniprot (the latter based on @ENASequence, part of open DNA) and to open up the results is great and have that part of @emblebi's service resources.
I have just seen the joy on the faces of scientists browsing the data in test mode (I am thinking about @Alexbateman1's face here in particular) and knowing how much information this will provide to scientists everywhere who are interested in structural biology
And the resource being open means that people can download and integrate into their own resources, from the well studied human proteome to, in the future, obscure bacteria and weird protists or viruses... which we might just need to known about in the future!
@emblebi we're ... serious about open data being available for all (globally; academic and commercial) - we allow for time-based embargos for publication, and we work with Data Access committees for honour the consents of human patient/individual data, but no other restrictions.
I know the release of alphafold.ebi.ac.uk will change how protein structure is brought in across science. It is a new tool for structural biologists, alongside their experiments; it is a resource for biologists to dip into structures.
Many many thanks to @demishassabis, John Jumper and the AlphaFold team @DeepMind - for going after a hard problem with no fear; for holding yourself to a high standard of science; for making the results open. You rock.

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More from @ewanbirney

28 Jun
*trumpets* A new preprint by colleagues in @PHE_uk from @isaperena's group and myself (my first infectious epidemiology paper!) on single source transmission of COVID19 using viral genotyping to understand relative risk of transmission settings. papers.ssrn.com/sol3/papers.cf…
Background; we have known for a long time that there is overdispersion of SARS-CoV-2 transmission; some estimates are that 20% of settings/events account for 80% of transmission. Understanding where these transmission events occur is important for non-pharmaceutical interventions
Furthermore, if we can be confident of spotting these individual small-scale super-spreading events and inform other individuals who are at risk of infection at the same time we can highlight people who are at the higher risk for infection, eg, asking them to get a test.
Read 23 tweets
21 Jun
A group of us (@minouye271, @JenniferRaff, @aylwyn_scally @AdamRutherford and myself) have written a piece on the language we use in genetics; untangling from previous sometimes racist language and being more precise and less harmful. We welcome feedback. arxiv.org/abs/2106.10041
There are some straightforward 'stop using this term' aspects (the use of "Caucasian" for example); there are some complex "what does this term mean" (ethnicity labels, the ethnicity/race duality in US vs just ethnicity in UK / Europe) and then technical stuff on GWAS >>
The technical piece is about how we describe the common place GWAS protocol of subselecting a group people in cohorts for association analysis; a reminder that the standard process has two steps to achieve pseudo-randomisation of non-genetic factors to genetic factors
Read 14 tweets
15 Jun
More thoughts post the extension of Stage 3 in the UK on COVID restrictions to July 19th.
Not enough in the press in my view is made of the change in *biology* of the virus; the virus is both more transmissible *and* is less dampened by 1st doses (in particular Ox/AZ, but Pfzier also) >>
This means that current UK population, both the number of 1st doses and where the 1st dose window is is a far harsher transmission environment for the Alpha and other variants than Delta; we've seen this play out in the numbers
Read 19 tweets
14 Jun
Sitting in softly air conditioned room on the Genome Campus, Cambridgeshire hot and sunny outside, musing about Corona this week. TL;DR - the UK looks like it is sensibly going to delay; the Delta variant is more transmissible and this implies at least one more wave worldwide.
Context: I am an expert in genetics and computational biology; I know experts in viral genomics, infectious epidemiology, clinical trials and immunology. I have COIs - I am a longstanding consultant to Oxford Nanopore and I was on the Ox/Az trial
Reminder: SARS-CoV-2 is high infectious virus which causes a severe disease, COVID, in a subset of people, often leading to death. No healthcare system in the world could cope with unfettered transmission of the virus, so a variety of control measures have been performed
Read 16 tweets
6 Jun
It's been a hot half term in the UK; at the end of this week here are my thoughts on Coronavirus. TL;DR the delta variant has changed the calculus in the UK but we don't know how much the vaccination calculus makes this less of a concern. Still more concern globally than UK.
Context: I am an expert geneticist + computational biologist; I know experts in infectious epidemiology, viral genomics, immunology and clinical trials. I have COIs. I am long established paid consultant to Oxford Nanopore and I am on Oxford/AZ clinical trial
Reminder: SARS-CoV-2 is an infectious virus which causes a horrible, sometimes lethal, disease; COVID. Left unchecked every healthcare system would not be able to process the number of diseased individuals.
Read 21 tweets
15 May
A Covid view, back in lovely Northumberland. TL;DR - Europe continues to vaccinate; UK, further in vaccination, has some concerning outbreaks associated with imported strains from India; much of the world continues to worsen with lack of vaccine supply.
Context: I am an expert in human genetics and computational biology. I know experts in infectious epidemiology, viral genomics, clinical trials, immunology. I have COIs: I am paid consultant to Oxford Nanopore and I was on the Ox/Az vaccine clinical trial.
Reminder: SARS-CoV-2 is an infectious virus which causes a horrible disease, COVID19, in a subset of people often leading to death. If we let the virus transmit unimpeded many people would die/hospitalised; no healthcare system could cope with the rate of hospitalisation.
Read 31 tweets

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