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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
hi,
german newsticker says about the fastest IBM cluster "BlueGene/L": http://www.heise.de/newsticker/meldung/59029 "Die schnellste Rechenanlage der Welt ist derzeit das IBM-Modell BlueGene/L, das mit 70,72 Teraflop/s für die Proteinforschung eingesetzt wird." translated: "now fastest cluster is IBM bluegene/l with 70 tflops, that _is used in protein research_" what does this thing do? or is it used to research our results? greetings, tom btw: i dont like that "stranger" on the left! a "stranger" would not have brought about 40 results... |
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
Hi Tom --
Thanks for bringing this to the forums. I found a similar information in a bulletin published on the web by BioIT at http://www.bio-itworld.com/news/041805_report8136.html. My understanding of this will be quite simplistic because I am not a computational research scientist or a biologist. From what I can gather from what was written, the article spotlights the publication of the first paper based on molecular dynamic simulations run on IBM's supercomputer Blue Gene/L run at the Computational Biology Center at the IBM T.J. Watson Research Center. The paper, published in http://www.bio-itworld.com/news/041805_report8136.html, described molecular interaction of a protein rhodopsin embedded in a bi-layer system containing cholesterol and two different lipids (I think we would call this as a membrane). From my meager understanding, this is a simulation of a specific protein in a complex environment. The Human Proteome Project that we are participating in here at the World Community Grid is studying the likely foldings of the many proteins found in the human system without the involvement of other complexities of the environment within which the protein exists. I would expect that the results of The Human Proteome Project might lead to other simulations such as this one. I am going to ask the staff of the World Community Grid to move this thread into the Human Proteome Folding forum which is monitored by some of the research scientists at the Institute For Systems Biology. Perhaps one of them might care to comment on this. |
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
Here is a supercomputer article that came out today - http://www.cnn.com/2005/TECH/04/26/supercomputer.space.reut/index.html
It's about a low-power 27 TFLOPS supercomputer that only needs 150 kilowatts. It includes the URL for http://www.top500.org which lists the top 500 supercomputers. None of our computers will ever make the list, but by using many computers we can compete on results. |
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
Hi Tom -- Thanks for bringing this to the forums. I found a similar information in a bulletin published on the web by BioIT at http://www.bio-itworld.com/news/041805_report8136.html. My understanding of this will be quite simplistic because I am not a computational research scientist or a biologist. From what I can gather from what was written, the article spotlights the publication of the first paper based on molecular dynamic simulations run on IBM's supercomputer Blue Gene/L run at the Computational Biology Center at the IBM T.J. Watson Research Center. The paper, published in http://www.bio-itworld.com/news/041805_report8136.html, described molecular interaction of a protein rhodopsin embedded in a bi-layer system containing cholesterol and two different lipids (I think we would call this as a membrane). From my meager understanding, this is a simulation of a specific protein in a complex environment. The Human Proteome Project that we are participating in here at the World Community Grid is studying the likely foldings of the many proteins found in the human system without the involvement of other complexities of the environment within which the protein exists. I would expect that the results of The Human Proteome Project might lead to other simulations such as this one. hi carroll (?), thank you for that info! i understand just very little of thas proteome things... i only wanted to know what WCG is related to that bluegene computings is, *if* it is. I am going to ask the staff of the World Community Grid to move this thread into the Human Proteome Folding forum which is monitored by some of the research scientists at the Institute For Systems Biology. Perhaps one of them might care to comment on this. thank you. i guess it would be interesting to other users, too. tom |
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
Hi LaberHanneS,
I may be wrong, but as far as I know, computers have been folding individual proteins for more than a decade, but the Human Proteome Folding project is the very first project in history to try to fold the proteins expressed by a genome. It is only recently that DNA sequencing has begun listing the entire genome of a species. Somebody had to be first. We are the leaders. [There are a number of limitations. For example, we are only folding short proteins <= 150 amino acids long. Pioneers always lack sophisticated abilities, which come later.] mycrofth |
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Viktors
Former World Community Grid Tech Joined: Sep 20, 2004 Post Count: 653 Status: Offline Project Badges:
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Just my 2 cents more on this subject. The Blue Gene computer is really a general purpose supercomputer. It was used to study the mechanics of protein folding and other protein processes in great detail. You can think of it as simulating the individual atoms and electrical and chemical interactions among them to try to duplicate what really happens in nature.
The Human Proteome Folding project on World Community Grid uses the Rosetta program. This program was developed over many years to encode higher level rules about how proteins tend to fold and has been verified to fairly reliably predict the correct folds. Using Rosetta, scientists can figure out generally what shape a protein folds into rather quickly, versus the more detailed and time consuming simulations mentioned above. Thus, for the first time, it is now feasible, using grid computing, to do this for all of the genes. |
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