PlanetQuest Update

Laurence Doyle posted a new update early this morning on PlanetQuest, saying:

I applied for the NASA Kepler Science Team and included PlanetQuest as the educational component of the proposal. I proposed to find planets in the multiple star systems that Kepler observes and won the proposal.

So, there will be NASA Kepler spacecraft data in the PlanetQuest Collaboratory (we'll divvy it up evenly) to look for planets in. What is amazing about these data is that the precision will be 100 times anything achieved on Earth -- that is, the detection of Earth-sized planets around Sunlike stars will be possible.

So this seems like good news for both Dr. Doyle's PlanetQuest efforts and the Kepler Mission, both of which are projects that I've been interested in for a very long time.

Now, if PlanetQuest can just get their software out the door and into my grubby little hands....

PlanetQuest Update

Another update from Dr. Laurance Doyle on the status of the PlanetQuest group:

...Our lack of progress at the moment is a funding issue which we feel could be solved if we can get initial funding to a point where we can finish the alpha test version of the software and thereafter sign folks up to be supporting-founding members of PlanetQuest.

We do have sufficient astronomical data (stellar light curves) at present for a thorough test of the system and could accommodate perhaps up to 100,000 users for a year. This was previously my main concern. We have also carried the problem through from data acquisition to light curve model fitting (the transit detection algorithm) and therefore see no technical issues in the way of proceeding.

Most of our personnel, however, are also extremely busy people working in other businesses and on other projects, and so PlanetQuest has not received the attention lately that it needs to move forward as quickly as it could, because it is largely (although not entirely) a volunteer project at this point.

I would like to see it take off this year-that is, that we are able to release an alpha version of the Collaboratory and start to post key parts of our educational web site on a daily basis. I am involved in fund raising for PlanetQuest at present, and also writing a comprehensive business plan.

The overall project in execution is quite complex, but the basic overview ideas are readily understandable. After about seven years now since the initial idea, we are still unique in offering a project like PlanetQuest (which surprises me a little). Computational speed (i.e., Moore's Law) has gone up over a factor of 25 in that time, so we have had to collect a lot more stellar data. Our team is ready to proceed, then, as soon as we can get support for the final phase of the programming...

PlanetQuest is a worthy project to allow desktop users (like me and you) to contribute to the search for extra-solar planets that may harbor life. But in order to get the software working and continue their science, they need money. I gave them some a while back, but they obviously still need more.

A New Way to Do Research from Home

I've blogged on a number of occasions about distributed computing, which allows you to contribute your unused computing power to advance scientific research, because I think that's the single biggest thing most of us can do right now to improve the state of science and technology.

But now you can do even more. The Folding@Home project at Stanford University has new client software for their protein folding simulation that will allow it to run on a Sony PlayStation 3.

According to the Folding@Home website, with about 10,000 PS3s online, the researchers would be able to achieve performance on the petaflop scale. With software from Sony, the PlayStation 3 will now be able to contribute to the Folding@Home project, pushing Folding@Home a major step forward.

Rosetta@home Branches Out

The Rosetta@home project (which I blogged about in December) has branched out from its original mission of predicting protein structures. David Baker reports in the Rosetta blog that they are working on a way to convert carbon dioxide into simple sugars using enzymes computationally engineered using Rosetta@home.

David writes:

Graduate student Justin Siegal and postdoc Eric Althoff have come up with a very clever new reaction cycle using new enzymes we would collectively engineer that in total carries out the following reaction:

2C02 + 2e- + H20 -> C2O3H2 + O2

the product is a simple sugar that could be used in a variety of ways, and the removal of C02 from the atmosphere would be great for countering global warming. A nice thing about this compared to current ideas of forming inorganic carbonate compounds is that it requires no other inputs. However, it does require electrons, and hence a source of energy. We are currently assessing the energy requirements of this process and comparing them to those of other proposed carbon sequestration mechanisms.

PlanetQuest Update

I received an email today from Dr. Laurance Doyle, who (among other things) serves as the President of PlanetQuest. PlanetQuest is a nonprofit 501(c)(3) organization whose mission is to inspire global participation in the discovery of planets.

Their goal is to launch a distributed computing project using the BOINC platform that I've blogged about here before. Their software--dubbed Collaboratory--will analyze data from telescopes focused on extremely dense star regions, such as the center of the galaxy in Sagittarius in the hopes of finding planets around other stars.

From their website:

Discovering a new delta Scuti star, for example, will help astronomers better understand the stability of stars; a new Cepheid variable star would help astronomers determine how far away stars are. Most exciting of all, you could discover a new planet—a never-before-seen world beyond our solar system! You will be credited for your discovery, and your find will be entered into the PlanetQuest catalog.

Dr. Doyle's email (which came in response to my donating money toward their work on the software) contained some information on the status of their work on the software. The information was long overdue, as they haven't done a very good job of keeping the public up-to-date on their progress (although they have responded to email requests for information). Dr. Doyle writes:

We have the eclipsing binary system classifier running very well, and are now interfacing the circum-binary planet discriminator with the the binary classifier. We'll soon be going straight onto the BOINC platform with this and at that time can release an alpha version of the Collaboratory. The beta should not be far behind with a ready number of testers interested in helping us, and we are shooting for this summer to release the beta test.

Project Profile: ClimatePrediction.Net

This week's project profile is for ClimatePrediction.net, a massive project to model and forecast weather in the 21st Century.

The software, like the other projects profiled so far, operates on the BOINC platform for distributed computing. The ClimatePrediction.net system uses the unused background cycles of its members' computers to simulate a large number of possible climate scenarios to determine how each individual variable affects the overall climate picture.

These simulations are then studied individually and merged together into one and tweaked as additional data becomes available. The more data runs that are performed, the more accurate the models will become.

Accurate prediction of climate change could be vital on both the short- and long-term scales. For example, more precise climate modeling could have shown that Hurricane Katrina would strike New Orleans, rather than the predicted path that showed it striking Texas. Advanced warning could have led to better evacuation and preparation and given people an expectation of the damage before it happened.

Similarly, in the long-term time scale, climate change predictions can give us better understanding of potential warming effects such as rising ocean levels, increased storm activity, etc.

If you're interested in participating in this type of science project, you can download the software here.

Project Profile: Seti@Home

This week's profile is for the SETI@home project, probably the most famous of all distributed computing software projects and the one that gave birth to the BOINC system.

In case you didn't already know, the SETI@home software is a distributed computing project that combs through massive amounts of data returned by radio telescopes (including the famous telescope at Arecibo) in search of signals that could have an intelligent origin. Due to the enormous amounts of data these telescopes collect, the need for computing power to analyze it is immense, and thus the idea of distributed computing was born.

I don't run SETI@home at the moment, although I did run the original SETI@home application many years ago (now called SETI@home classic). I think SETI's methods are somewhat limited, in that they only scan a very narrow band of data, and only radio waves. Any advanced society attempting to communicate would likely use a different method, so I put my computing resources into other projects. I'm not one to only push the projects that I support, however, so if searching for signals from aliens is your thing, go ahead and head to their website and get the software.

Project Profile: Rosetta@home

This week's profile is for the Rosetta@Home project. Rosetta@home uses the BOINC software platform for distributed computing to determine the 3-dimensional shapes of proteins in research, with the stated goal of finding cures for some major human diseases.

Basically, by running the BOINC software and setting up the Rosetta@home project, your wasted CPU cycles can be put to use helping cure some of the most devastating diseases affecting humans today, such as cancer and Alzheimer's disease.

From the Rosetta@home Science FAQ:

What is Rosetta?

Rosetta is a protein structure prediction and design program.

What is a protein?

A protein is a polymer of amino acids that is encoded by a gene.

What are amino acids?

Amino acids are chemical moieties that form the basic building blocks of proteins. There are 20 different amino acids that are specified by the genetic code. These 20 amino acids fall into different groups based on their chemical properties: acidic or alkaline, hydrophilic (water-loving) or hydrophobic (greasy).

What do proteins do?

Proteins perform many essential functions in the cells of living organisms. They replicate and maintain the genome (DNA), they help cells grow and divide, and stop them from growing too much, they give a cell its identity (eg liver, neuron, pancreatic, etc.), they help cells communicate with each other. Proteins, when mutated or when affected by toxins can also cause disease, such as cancer or alzheimer's. Bacterial and viral proteins can hijack a cell and kill it. In short, proteins do everything.

How do proteins perform all their different functions?

Each protein folds into a unique 3-dimensional shape, or structure. This structure specifies the function of the protein. For example, a protein that breaks down glucose so the cell can use the energy stored in the sugar, will have a shape that recognizes the glucose and binds to it (like a lock and key). It will have chemically reactive amino acids that will react with the glucose and break it down, to release the energy.

Why do proteins fold into unique structures?

It's long been recognized that most for most proteins the native state is at a thermodynamic minimum. In English, that means the unique shape of a protein is the most stable state it can adopt. Picture a ball in a funnel - the ball will always roll down to the bottom of the funnel, because that is the most stable state.

What forces determine the unique native (most stable) structure of a protein?

The sequence of amino acids is sufficient to determine the native state of a protein. By virtue of their different chemical properties, some amino acids are attracted to each other (for example, oppositely charged amino acids) and so will associate; other amino acids will try to avoid water (because they are greasy) and so will drive the protein into a compact shape that excludes water from contacting most of the amino acids that "hide" in the core of this compacted protein.

Why is it so difficult to determine the native structure of a protein?

Even small proteins can consist of 100 amino acids. The number of potential conformations available to even such a (relatively) small protein is astronomical, because there are so many degrees of freedom. To calculate the energy of every possible state (so we can figure out which state is the most stable) is a computationally intractable problem. The problem grows exponentially with the size of a protein. Some human proteins can be huge (1000 amino acids).

So how does Rosetta approach this problem?

The rosetta philosophy is to use both an understanding of the physical chemical properties different types of amino acid interactions, and a knowledge of what local conformations are probable for short stretches of amino acids within a protein to adopt, to limit the search space, and to evaluate the energy of different possible conformations. By sampling enough conformations, Rosetta can find the lowest energy, most stable native structure of a protein.

Why is distributed computing required for structure prediction by Rosetta?

In many cases where the native structure of a protein is already known, we have noticed that Rosetta's energy function can recognize the native state as more stable than any other sampled state. When starting from a random conformation, however, we've observed that the native state is never sampled. By applying more computing power to the problem, we can sample many more conformations, and try different search strategies to see which is the most effective.

How will Rosetta@home benefit medical science?

Please see our Disease Related Research page for information on how Rosetta is being applied to medical problems.

Processing Power

While you sit reading this blog, your computer's processor is probably sitting mostly idle. Today's computer processors are monsters when it comes to number-crunching capability, and they have to be in order to process the multimedia explosion that drives our modern society. This is especially true when it comes to computer games, which continue to tax even the most powerful systems available today with their advanced graphics, positional and dynamic audio, and artificial intelligence.

But when you're not playing high-end video games, most of that processing power sits idle. It's like the difference between driving your computer down the interstate at (or close to) top speed versus sitting at a stop light waiting to go. Your engine is still running, but it's not accomplishing anything.

With computers, though, that doesn't have to be the case. Those spare CPU cycles can be put to use for any of a large number of tasks, including searching for signals from aliens, simulating the folding of proteins to better understand the causes of diseases (and find potential cures), simulating weather to help create better predictive methods, search for spinning neutron stars by processing data from LIGO and GEO gravitational wave detectors, or many other projects.

The software that runs these projects is called BOINC, and it is designed to run in the background, using only the spare processing power. It doesn't interfere with your computer's normal processes, because it sets itself up to run in the lowest priority setting on your computer.

It doesn't cost you anything to run BOINC, and it may just help some advance some research project toward curing a disease or furthering our understanding of the universe around us.