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Gamers Beat Algorithms At Finding Protein Structures
jamie writes "Researchers have turned the biochemical challenge of figuring out protein folding structures into a computer game. The best players can beat a computerized algorithm by rapidly recognizing problems that the computer can't fix. From the article: 'By tracing the actions of the best players, the authors were able to figure out how the humans' excellent pattern recognition abilities gave them an edge over the computer. For example, people were very good about detecting a hydrophobic amino acid when it stuck out from the protein's surface, instead of being buried internally, and they were willing to rearrange the structure's internals in order to tuck the offending amino acid back inside. Those sorts of extensive rearrangements were beyond Rosetta's abilities, since the energy changes involved in the transitions are so large.'"
I thought Foldit was actually a pretty fun game and a great idea when it came out, and now that I'm reminded of it I'll have to go back and play some more. It's fantastic to have validation that humans are still excellent pattern recognition engines compared even to very modern algorithms and powerful computers.
But to extend the idea more generally, seems rather hard. Foldit had the great insight to take you to an algorithmically close starting place and let you complete the final adjustments - in that way the algorithm itself is as much a part of the team as the detail or adjustment members they were talking about.
I wonder how many other ideas can be so easily brought to a place close enough that a human can recognize patterns enough to be of use in a final solution. I look forward to seeing what astronomers come up with...
"There is more worth loving than we have strength to love." - Brian Jay Stanley
When humans have figured out how to connect their own brains in beowulf cluster, to harness the awesome power of the human mind, 30% of world population is going to be slave to corporations that need human brain power to do their bidding in order to do whatever that they do. But that's pretty much the same as it is now. But on the other side it really could be a nice job opportunity, go to work turn your brain on to some cluster be unconscious for 8 hours and go back home.
That was exactly the kind of thing I was looking for to see how the ideas would translate to astronomy...
However the clients (or at least the client I tried) are not great. One of the nice things about Foldit was the UI for manipulations was really well thought out and made it easy to manipulate a pretty complex 3D object, also easy to undo flawed changes. In the galaxy matching game at the link you, had, I got one galaxy pair close to a match but one of the galaxy had spiral arms reversed from the real image, that I could not figure out how to correct for - and then after I clicked on "mass" the whole thing became an oval instead of a spiral, and would not revert no matter how I adjusted things.
I hope they are seeking some funding to expand work on clients for that because they could get some useful analysis from that I think.
"There is more worth loving than we have strength to love." - Brian Jay Stanley
The really funny part is that somebody programmed a bot to play the game, and it's doing better than the researcher's algorithm.
Anthropic principle: We see the universe the way it is because if it were different we would not be here to see it.
While technically true, pattern recognition is the core of our intelligence.
More accurate to say that your intelligence lays in other areas than spacial recognition.
Mod me down with all of your hatred and your journey towards the dark side will be complete!
It's all over their parents basement.
Score: -1 Eeewwww
Table-ized A.I.
Seth Cooper, Firas Khatib, Adrien Treuille, Janos Barbero, Jeehyung Lee, Michael Beenen, Andrew Leaver-Fay, David Baker, Zoran Popovi & Foldit players
So if you've played Foldit you have helped with the authorship of this paper. Not only that, but since it is a biological paper, you are a corresponding author (by virtue of being the last name on the list).
I would highly recommend listing that on your CV, or at least in your application to the Nobel Committee.
Damn_registrars has no butt-hole. Damn_registrars has no use for a butt-hole.
Sweet, I'll put that right after "Time's Person of the Year 2006".
forget about Foldit! Just download Folding@Home and let your CPU/GPU do it for you!
FoldIt and Folding@Home are doing completely different things. FoldIt (or more specifically, the Rosetta software underneath it) is attempting to guess the final structure of novel protein sequences, using a variety of clever tricks such as mining the database of known structures for peptide motifs. It contains energy functions to evaluate candidate structures, but it is not simulating physical processes, and it tells you nothing about how the linear chain of amino acids forms the 3D structure. Folding@Home is used to study the process of protein folding, where the end result is already known; it isn't useful as a structure prediction tool. Both programs require a massive amount of computing power, but for very different reasons. Both are very useful, but there is almost no overlap in their practical applications. (And it should go without saying that while they can both be an excellent complement to experimental studies, neither can replace them.)
Does that give me a an Erdos number?
Citation please?
Essentially, catalysts can help proteins fold- such as other proteins helping a polypeptide strand be arranged into a particular structure.
Two clarifications (rather than answers): Evidently, you mean chaperones that act by creating a confinement region (a cage) of boundaries (walls build of amino acids) of desired hydrophobicity distribution, where proteins of with improper conformations can get better. Protein atoms perform thermal movements so to a little degree they can search for an optimal conformation, but it's not enough - it seems that proteins are (sub)optimal by design (i.e. by evolution). I wrote sub~, because the global minimum POV is a hypothesis (and there may exist separated kinetic xor thermodynamic minima).
If the Andrew Leaver-Fay in this paper is the same one who cowrote "Faster placement of hydrogens in protein structures by dynamic programming" with Jack Scott Snoeyink, then yes. It gives a 4.
Best shot since I missed out on getting a 2 on Ebay.