191–200 of 683 posts
Pretty interesting that they only used about $15k worth of resources (retail price) to achieve this. It's not a technique that would have been out of reach for other organizations based only on not being able to afford the compute.
Whether it's good PR or not is to be debated, but it seems that the talent at DeepMind simply can accomplish things other's can't.
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AlQuraishi described the progress made in CASP13 (2018) as “two CASPs in one”. This one is an even bigger breakthrough.
I particularly like the rant on pharmaceuticals companies lack of basic research. My impression has been that medical progression have been slow for quite some time, nice to see that there are some truth to that. In the end software and tech companies might just eat up the pharmaceutical industry as well. - It's all just code at some level. The Deepmind team did this with ; "We trained this system on publicly availab…
Does it mean there is no point in playing fold.it anymore?
Not knowing a lot about biotechnology, I read the article and it sounds great, but how big is this as a gamechanger? Can someone comment on how big are the implications of this in, let’s say, 5 years from now, on day to day life? Does this mean that biotech is going to explode? Or just that drugs will come to market faster, perhaps cheaper for rare diseases, but from the same industry structure as always?
Getting from DNA structure from tissue samples is relatively straight forward. DNA -> RNA -> unfolded protein is basically one-to-one mapping in most cases. How protein functions depends on how it folds into itself. Once you solve protein folding, you can take DNA sample and see the structure of the molecule without working in lab using crystallography techniques. Solving protein folding is huge, Nobel in chemistry s…
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The forward folding problem lets you determine structures from a known genetic sequence. So for example you could very quickly sequence the genome of a virus and figure out how it worked much faster than current methods allow. The reverse folding problem lets you specify a structure and then make a genetic sequence to produce it. For example you could look at this virus to see how it infects its host, then design a c…
The set of all proteins which can potentially be expressed in an organism is known. Now maybe we also get decent (static) structure information for these. But the interaction of a virus with the host cell is much more complex. There is much more than just an amino acid sequence involved. And these parts are all moving, so a static picture as we now can create faster than before does not contain all the information ne…
Sure, "known", but it's on the order of 20^10000. It won't fit in the entire visible volume of the universe.
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you give pharma too much credit. I had built a previous system to do something similar to this that produced excellent results and tried to give it away for free to Genentech, which ignored me. They said it didn't work for their purchasing department.
I don't believe you, but I look forward to you showing proof of this with some links (and if you tried giving it for free, I assume you just open sourced the whole deal, so I look forward to a repo link or the like).
we offered the service for free to Genentech since I used to work there and knew they could probably use it to get some good publications.
We didn't open source the distributed computing framework, but the underlying technology (Folding@Home) is based on gromacs, which is open source. It's the scale at which it ran, and the processing pipeline for filtering the results that had the real value.
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How far does the similarity extend? Specifically, the big question for me is whether AlphaFold will be freely available like ImageNet, or proprietary.
I expect this to be quickly replicated once published. Training data is public and training compute is not enormous and AlphaFold of 2018 did get replicated.