Re: Wow: AlphaFold .ipynb and Google Colab

[David Szent-Györgyi]

AlphaFold is an extraordinary advance in the speed of the development of 
knowledge. Compare the rapidity of the understanding of the structure of 
COV-2 with the decades of labor required in the 1950s and 1960s for 
determination of the structure of myosin, the protein that is the largest 
constituent of skeletal muscle, as described in this article on the 
investigation of the molecular motor of muscle 
. 

(No, I'm not a biochemist; my parents were - they spent their working lives 
on the regulation of muscle contraction). 

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Re: Wow: AlphaFold .ipynb and Google Colab

[David Szent-Györgyi]

My day job is technical support for basic research in life science, and 
abuts drug discovery, which is targeted work. Below is a note that I sent 
to my colleagues at the end of 2020, when last winter's COVID outbreaks 
were at a terrible high. 

--- note begins ---
This is really interesting work in life science and work in drug discovery, 
driven by computation:

>From <
https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology
>:


*. . . In the meantime, we’re also looking into how protein structure 
predictions could contribute to our understanding of specific diseases with 
a small number of specialist groups, for example by helping to identify 
proteins that have malfunctioned and to reason about how they interact. 
These insights could enable more precise work on drug development, 
complementing existing experimental methods to find promising treatments 
faster.We’ve also seen signs that protein structure prediction could be 
useful in future pandemic response efforts, as one of many tools developed 
by the scientific community. Earlier this year, we predicted several 
protein structures of the SARS-CoV-2 virus, including ORF3a, whose 
structures were previously unknown. At CASP14, we predicted the structure 
of another coronavirus protein, ORF8. Impressively quick work by 
experimentalists has now confirmed the structures of both ORF3a and ORF8. 
Despite their challenging nature and having very few related sequences, we 
achieved a high degree of accuracy on both of our predictions when compared 
to their experimentally determined structures.*

An associated video:


--- note ends ---

>

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Re: "Random" de-hoist

[Edward K. Ream]

On Monday, September 6, 2021 at 9:13:34 PM UTC-5 Phil wrote:

>  I had a "random dehoist" again. Here's the sequence of events I captured. 
> [snip]
>

Do you ever use chapters? 

Edward

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Re: Wow: AlphaFold .ipynb and Google Colab

[Edward K. Ream]

On Tue, Sep 14, 2021 at 1:05 PM jkn  wrote:

The link to the PDF worked for me, thanks
>

You're welcome :-) Good luck chasing the white rabbit...

Edward

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Re: Wow: AlphaFold .ipynb and Google Colab

[jkn]

The link to the PDF worked for me, thanks

J^n


On Tuesday, September 14, 2021 at 4:20:51 PM UTC+1 Edward K. Ream wrote:

> On Tuesday, September 14, 2021 at 8:07:34 AM UTC-5 Edward K. Ream wrote:
>
> > I've converted the Alpha sources (almost all python) to a study outline. 
> I'll make it available once I finish editing it.
>
> Still true, but the "raw" python code is pretty much impenetrable. Heh, I 
> had to reread the Nature article to verify that yes, neural networks  *are 
> *involved. The article says so right at the beginning, but I have not yet 
> discovered where the neural networks make their appearance in the code!
>
> In effect, the supplementary data for the article contains the code's 
> theory of operation:
>
> https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-021-03819-2/MediaObjects/41586_2021_3819_MOESM1_ESM.pdf
>
> Not sure if this .pdf file is freely available. I can send it to anyone 
> who is interested.
>
> The supplementary .pdf is *not* easy reading. Probably one needs multiple 
> PhD's to understand it.
>
> Edward
>

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Re: Wow: AlphaFold .ipynb and Google Colab

[Edward K. Ream]

On Tuesday, September 14, 2021 at 10:20:51 AM UTC-5 Edward K. Ream wrote:

The supplementary .pdf is *not* easy reading. Probably one needs multiple 
> PhD's to understand it.
>

Here are the supplementary videos that we mortals can enjoy.

Supplementary Video 1 


Video of the intermediate structure trajectory of the CASP14 target T1024 
(LmrP) A two-domain target (408 residues). Both domains are folded early, 
while their packing is adjusted for a longer time.
Supplementary Video 2 


Video of the intermediate structure trajectory of the CASP14 target T1044 
(RNA polymerase of crAss-like phage). A large protein (2180 residues), with 
multiple domains. Some domains are folded quickly, while others take a 
considerable amount of time to fold.
Supplementary Video 3 


Video of the intermediate structure trajectory of the CASP14 target T1064 
(Orf8). A very difficult single-domain target (106 residues) that takes the 
entire depth of the network to fold.
Supplementary Video 4 


Video of the intermediate structure trajectory of the CASP14 target 
T1091. A multi-domain target (863 residues). Individual domains’ structure 
is determined early, while the domain packing evolves throughout the 
network. The network is exploring unphysical configurations throughout the 
process, resulting in long ‘strings’ in the visualization.

Edward

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Re: Wow: AlphaFold .ipynb and Google Colab

[Edward K. Ream]

On Tuesday, September 14, 2021 at 8:07:34 AM UTC-5 Edward K. Ream wrote:

> I've converted the Alpha sources (almost all python) to a study outline. 
I'll make it available once I finish editing it.

Still true, but the "raw" python code is pretty much impenetrable. Heh, I 
had to reread the Nature article to verify that yes, neural networks  *are 
*involved. 
The article says so right at the beginning, but I have not yet discovered 
where the neural networks make their appearance in the code!

In effect, the supplementary data for the article contains the code's 
theory of operation:
https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-021-03819-2/MediaObjects/41586_2021_3819_MOESM1_ESM.pdf

Not sure if this .pdf file is freely available. I can send it to anyone who 
is interested.

The supplementary .pdf is *not* easy reading. Probably one needs multiple 
PhD's to understand it.

Edward

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Re: Leo for VSCode: LeoInteg 0.1.19 beta Released!

[Edward K. Ream]

On Mon, Sep 13, 2021 at 10:08 PM Félix  wrote:

*Leonistas: here's a fourth, and hopefully last, beta version for you to
> test! *
>

Many thanks for this new version. Installation went smoothly. I like the
feedback about updates and settings. The console window stays closed :-)

Edward

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Re: Leo 6.4 b3 and 6.4 final coming soon

[Edward K. Ream]

On Tue, Sep 14, 2021 at 9:26 AM Edward K. Ream  wrote:

> I'll update leoserver.py so it defines __version__ in terms of the
version tuple.

Done in devel at 97db83.

Edward

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Re: Leo 6.4 b3 and 6.4 final coming soon

[Edward K. Ream]

On Tue, Sep 14, 2021 at 9:22 AM Edward K. Ream  wrote:

> Perhaps the client could ask the server for the server version, say a *version
tuple* like (1, 0, 0). This would allow clients to warn if some features
depend on later versions of the server.

I'll update leoserver.py so it defines __version__ in terms of the version
tuple.

Félix, if it's alright with you I'll delegate to you the task of having the
server respond to a query about the version.

Edward

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Re: Leo 6.4 b3 and 6.4 final coming soon

[Edward K. Ream]

On Mon, Sep 13, 2021 at 8:43 PM Félix  wrote:

I'm not sure what to do next in the short term : I cant reproduce what
> Alexey / Gaurami reported : the text selection range bug...!

...

> So , I'm using leoInteg relatively bug-free for long sessions wondering
> why the heck dont I just release this version I've got going as 1.0 instead
> of 0.1.19 beta ...?
>
I'm still working on a few bugs for Leo 6.4 b3, so releasing 0.1.19 beta
seems reasonable.

So here's what I'll do: I'll release 0.1.19 right now tonight - and I'll
> release 1.0 (without changes if nothing pops up) along you with 6.4 so
> they're released the same day.  (I'll keep the issue open on github about
> the selections range.)
>

I agree with this plan. It's time to get the code out the door!

I am dealing with my own difficult-to-pin-down bug. I'll do my best in the
next few days, but I'm not going to delay either Leo b3 or final for the
bug.

One thought about compatibility. Perhaps the client could ask the server
for the server version, say a *version tuple* like (1, 0, 0). This would
allow clients to warn if some features depend on later versions of the
server.

For example, suppose the 'extract' bug ends up requiring leoserver 1.1. The
client could warn if the leoserver is 1.0 and degrade gracefully.

Right now the server defines a __version__ constant. Perhaps this should be
composed from the version tuple.

*Summary*

Thanks for your work trying to track down the extract bug. Imo, this bug
isn't remotely serious enough to delay leoInteg 1.0.

Imo, the server should be able to report the version tuple, but right now I
see no need for the client to do anything with the version.

What do you think?

Edward

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Re: Wow: AlphaFold .ipynb and Google Colab

[Edward K. Ream]

On Tue, Sep 14, 2021 at 6:03 AM Alexey Tikhonov 
wrote:

> Wow! Thanks for sharing!
>

You're welcome. I've converted the Alpha sources (almost all python) to a
study outline. I'll make it available once I finish editing it.

Edward

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Re: Wow: AlphaFold .ipynb and Google Colab

[Alexey Tikhonov]

Wow! Thanks for sharing!

понедельник, 13 сентября 2021 г. в 21:16:22 UTC+7, Edward K. Ream: 

> AlphaFold (See this Nature article 
> ) solves one of the 
> grand challenges in computational science.  Full sources for AlphaFold are 
> available here .
>
> The AlphaFold sources contain  AlphaFold.ipynb 
> , 
> a Jupyter notebook.The FAQ in the notebook contains a reference to Google 
> Colab. OMG!  Take a look at the Colab FAQ 
> !
>
> "Colab allows anybody to write and execute arbitrary python code through 
> the browser, and is especially well suited to machine learning, data 
> analysis and education. More technically, Colab is a hosted Jupyter 
> notebook service that requires no setup to use, while providing free access 
> to computing resources including GPUs."
>
> !
>
> Edward
>

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