i'm noob in these, but i'm thinking that a lower energy fold minima may in some cases be possible but it may 1st need to transit to a 'higher energy' barrier to reach an even lower energy minima. if this is true i'd guess nature may after all settle for 'higher energy' minima? lol

Interesting but going slow.

clusters of arm chips would not match the top tier haswell or skylake gflops v energy requirements (gflops per watt)

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Not sure this sounds like a "proper" GA. Do you have a paper/documentation on this?

Thanks

I actually think this is a "proper" GA. Appears they seek a "folding model" and the best way is to create a population of models. Models that perform the best are kept and mutated to see if the mutation is better or worse. Appears the goal is to find a best fit model until near perfection is met. They will probably use it across a set of proteins to determine if the model can reach lowest energy state in every set. Not a bad approach. Happy to be crunching with PhD Baker.

Yes, that is a description of how GAs work. However, in the case of Rosetta they use simulated annealing methods (rather than GA methods) to find local (and hopefully global) minima. The end results of all these folds are amalgamated to produce a graph like this:-
(snipped)

So it hinges on what is meant by "These models are then recombined to create new population(s) of models iteratively." Like I said, doesn't sound "GA - y"

Maybe they should try a real GA rather than simulated annealing. The problem though with GA in this case is the "cost function". How are they going to define a cost function for a model?

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

Not sure this sounds like a "proper" GA. Do you have a paper/documentation on this?

Thanks

I actually think this is a "proper" GA. Appears they seek a "folding model" and the best way is to create a population of models. Models that perform the best are kept and mutated to see if the mutation is better or worse. Appears the goal is to find a best fit model until near perfection is met. They will probably use it across a set of proteins to determine if the model can reach lowest energy state in every set. Not a bad approach. Happy to be crunching with PhD Baker.

Does Rosetta use a genetic algorithm to find a lowest energy state? See "Genetic Algorithms in Search, Optimization and Machine Learning". by David E Goldberg.

Yes! On robetta we send off many individual jobs to create a population of models. These models are then recombined to create new population(s) of models iteratively.

https://www.sciencenews.org/article/art-dna-folding

could there possibly be n possible ways to fold it as well?

:o :D lol

http://www.popularme...ne-editing-lab/

This should be posted on the front page so people can see the research this project is doing thanks to the volunteers.

+1

Also, the Haswell generation (22nm) i7-5820k is a comparative bargain now at £250 for 6 cores so I'd go for that if I were in the market at the moment.

Really? I'd be interested at that price, where did you see it?

Newegg, but having looked further, it doesn't include VAT :(
http://www.newegg.com/global/uk/Product/Product.aspx?Item=N82E16819117402

Still, at £300 I'd go for it over the alternatives at the moment:
https://uk.pcpartpicker.com/part/intel-cpu-bx80648i75820k
http://www.aria.co.uk/Products/Components/Processors/Intel+CPUs/Core+i7+-+Socket+2011-v3+X99/Intel+i7-5820K+3.30GHz+%28Haswell-E%29+x6+Core+Processor+?productId=61708&source=pcpartpicker

Also, the Haswell generation (22nm) i7-5820k is a comparative bargain now at £250 for 6 cores so I'd go for that if I were in the market at the moment.

http://fossbytes.com...beam-splitting/

I have notice that there have not been a lot of updates to the websites news or twitter feed in the past couple of months. I always find it interesting to read what is going on behind the scenes but havnt been able to read it in a while. I was just wondering what kind of progress rosetta is making? How much has actually been discovered? Can we expect a lot of new protein materials or drugs to be coming in the near future as a result of rosetta?

Dont mean to be bothersome, would just like to know.

The executing code seems to be compiled for a i386 and uses the 387 floating point 8-register stack model. The code (on my machine) spends about 5% of the time waiting for the "fmul st0,st1" ("====" below) to complete.

minirosetta_3.54_windows_x86_64.exe

Rosetta instruction clip ...

address instruction
0x6b3d82 add ebx, ecx
0x6b3d84 lea ebx, ptr [edi+ebx*8]
0x6b3d87 fld st0, qword ptr [edi+eax*8]
0x6b3d8a mov eax, dword ptr [ebp-0x20]
0x6b3d8d mov edi, dword ptr [ebp-0x14]
0x6b3d90 fmul st0, st1
0x6b3d92 inc ecx =========================
0x6b3d93 add eax, 0x8
0x6b3d96 fsubr st0, qword ptr [ebx]
0x6b3d98 add edx, 0x8


All post-Pentium4 CPU (newer than Nov. 2000) support the SSE2 register model. Simply adding the SSE2 target option to the builds would require the machines to be made this century but would use the SSE registers. The 16 directly addressable registers would reduce register stores to the stack and code scheduling (less shuffling of data around and more computation).

A simple recompile should make a noticeable difference without any side effects. If you compile newer than SSE2 or GPUs, you have to start worrying about and managing the population of target machines you deliver workloads to.

Beyond that, the developers would need to look more closely at the code.