[FRIAM] Weighted Ensemble

[Marcus Daniels]

This week's Science has an article on predicting RNA structure using deep learning.    The other approach you mention sounds like Rosetta.

-----Original Message-----
From: Friam <friam-bounces at redfish.com> On Behalf Of u?l? ?>$
Sent: Monday, August 30, 2021 11:27 AM
To: friam at redfish.com
Subject: Re: [FRIAM] Weighted Ensemble

The below is the only thing my search turns up (via $ grep -i folding $(grep -li protein $(grep -l "From: [\"]*Roger Critchlow[\"]* <rec at elf.org>" *))) I found nothing if I include "parallel" in the and. If you have other keywords, maybe it'll be more apparent. (Header still includes Google. So it's not clear to me when you started using GMail.)


On 9/14/09 7:48 PM, Roger Critchlow wrote:
> As I read it, the issue isn't whether structures and/or configurations 
> are/aren't important, the question is whether they operate according 
> to emergent or resultant rule sets.
> 
> The Emergentists were betting heavily on the emergent rule set.  They 
> believed that the variety of chemistry couldn't possibly be the result 
> of protons and electrons operating according to physics as they knew 
> it.  They were right, it wasn't physics as they knew it, but the 
> answer turned out to be the result of configurational physics rather 
> than emergent principles of chemistry.  They also bet that the variety 
> of biology couldn't be the result of chemical molecules operating 
> according to the chemistry they knew.  And they were right again, it 
> wasn't chemistry as they knew it, but the answer turned out to be the 
> result of configurational chemistry rather than emergent priniciples 
> of biology.
> 
> Chemistry and biology turn out to be ever more complicated 
> configurations of protons and electrons, with some neutron ballast, 
> operating according to the principles of quantum mechanics and 
> statistical mechanics.  It's all physics, same particles, same forces, 
> same laws, no emergent forces.  There are configuration forces, but 
> they're not emergent forces, they're subtle results of electrons 
> packing themselves into quantized energy levels in increasingly 
> complicated configurations of nuclei.
> 
> The structure of DNA and the elaboration of molecular biology was the 
> last straw because it provided a purely physical mechanism for 
> inheritance.
> 
> But you're right to see it as a bit of a conundrum.  The Emergentists, 
> as McLaughlin summarizes them, were substantially correct:
> configurations of atoms in molecules are the key to understanding 
> chemistry, there are all sorts of chemically distinctive things that 
> happen because of those configurations, none of those chemically 
> distinctive things are obvious when you play around with protons and 
> electrons in the physics lab.  But it all turned out to be part of the 
> resultant of quantum mechanics, not emergent in the sense the 
> Emergentists had painted themselves into, so they were wrong in the 
> one sense they really cared about.




On 8/30/21 10:43 AM, Roger Critchlow wrote:
> This sounds like an algorithm for parallel protein folding that I 
> ranted about a long time ago.  Start with some collection of 
> conformations; perform many different molecular dynamics simulations 
> from your starting points in parallel;  continue with the most 
> promising subset.  As molecular dynamics on proteins tends to find 
> lots of deadends, you can get a lot of improvement by tabu'ing the 
> known deadends and extending into conformations which don't double 
> back into visited regions.  Seems I remember it went back to some monte-carlo work at LANL in the 1950's, Goodfellow?
> 
> It also sounds a lot like Monte Carlo Tree search as used, for 
> instance, in AlphaGo.
> 
> It boils down to how well you can distinguish promising and 
> unpromising branches.
> 
> Whatever, it was in Friam before gmail, so I can't search for it.  
> There doesn't appear to be any search in the Friam archives, and the 
> years before
> 2017 at https://redfish.com/pipermail/friam_redfish.com/ are all 404 anyway.
> 
> -- rec --
> 
> On Mon, Aug 30, 2021 at 12:39 PM uǝlƃ ☤>$ <gepropella at gmail.com> wrote:
> 
>> In my ignorance, I've thought of weighted ensemble (WE) as a specific 
>> kind of novelty search. E.g. weighting toward trajectories that 
>> exhibit anomalies. Is that what you mean by it?
>>
>> Also, for each of the 5 you're interested in, do you have convenient 
>> example cites for each/any of them? In particular, (2) and (3)? Or 
>> are these just ideas of places where you think WE should apply?
>>
>> For my part, no. I haven't used WE in particular. I have a friend 
>> who's worked on identifying mechanical anomalies from audio 
>> (recordings of machines as they hum). He may have used it. I'll ask.
>>
>> On 8/29/21 1:07 PM, Jon Zingale wrote:
>>> I am presently working on learning weighted ensemble <
>> https://arxiv.org/pdf/1906.00856.pdf> sampling techniques and was 
>> curious if any here have worked with them before. The technique seems 
>> promising and has enjoyed quite a bit of success (even above MCMC <
>> https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo>) in circles 
>> concerned with reaction rates for rare events.
>>>
>>> Some points of interest for me include:
>>>
>>>  1. A better sampling of fringe-outlier works/art from streaming
>> services.
>>>  2. An alternative (bin-based sampling) to globally defined "fitness"
>> measures in evolutionary modeling.
>>>  3. An application of diffusion-limited aggregation to general 
>>> search
>> (especially in the face of limited resources)
>>>  4. An application of linear logic to optimization problems in
>> conformation prediction <
>> https://en.wikipedia.org/wiki/Protein_structure_prediction>.
>>>  5. Investigation of dynamical properties, such as distribution of
>> trajectories with "high winding number", on strange attractors.
>>>
>>>
>>> While I am just beginning to grok the technique, I thought it might 
>>> be
>> fruitful to ask here.


--
☤>$ uǝlƃ

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