Search

Where do I check on the status, statistics, etc. for my Team Challenge (or a challenge my team is participating in)?

Just go to your My Team page, and scroll down to the Challenge Control Panel. All team members will see up to five Current and Upcoming Team Challenges (team captains will see Pending Team Challenges as well). If your team has more than five Current Team Challenges or more than five Upcoming Team Challenges, you may click the link at the bottom of the Challenge Control Panel to view your team's entire Team Challenge History. In the Challenge Control Panel or Team Challenge History View you may click on the name of the challenge to view more details about the challenge; for example: scores for all teams in the challenge, the names of the other teams participating in the challenge, and whether the challenge is open or not. The Team Challenge History page is where you may view your team's past challenges.

May I invite more teams to my Team Challenge after I issue it?

Once a Team Challenge has been issued (by pressing the submit button on the Issue Team Challenge page), no more teams may be invited. If you have issued an Open Challenge, other teams may still join the challenge up to the Start Date, or until the end of the challenge if you have chosen to allow Late Joiners (Late Joiners only get credit for statistics accumulated after joining the challenge).

What is a Team Challenge?

A Team Challenge is essentially a competition between teams to see which team can return the most results, or generate the most points or run time in a given time period. A Team Challenge can be open to all teams on World Community Grid, or limited to only teams invited by the challenge creator.

How do I create a Team Challenge that is open to all teams?

When on the Issue Team Challenge page, just give your Team Challenge a name, check the box labeled "Open Challenge?", enter dates for your Team Challenge, select a type of challenge, and click the submit button. Done!

You can invite teams to an Open Challenge if you'd like. This will insure that your challenge invitation shows up in the team captains Pending Challenges under the Challenge Control Panel. If the team captain has chosen to receive Team E-mails (via the My Profile page) they will also receive an e-mail informing them of your newly created Team Challenge.

How do I create a Team Challenge that is just limited to certain teams?

When on the Issue Team Challenge page, just give your Team Challenge a name, enter dates for your Team Challenge, select a type of challenge, and invite at least one other team. Inviting teams is as simple as searching for a team name, and clicking the link to "Invite This Team." You may do a search, invite some teams, and then do another search to get a broad array of teams to invite to your challenge.

How do the Increase in XXXX challenges work?

The Increase in XXXX challenges, can also be viewed as "percent increase" challenges. In these challenges, a baseline is calculated based on the recent daily average production for each team in the challenge. During the challenge, the daily team statistics are averaged for the current duration of the challenge and then the baseline average is subtracted to yield an average increase (or decrease). That average increase/decrease is divided by the baseline average to determine the percent increase/decrease. For example, if a team averages 3 days of Run Time per day leading up to the challenge, and then averages 4 days of Run Time during the period of the challenge, the percent increase would be 33%. The math would be: (4-3)/3.

The final winner of the challenge will be the team with the largest percent increase over their baseline average.

How will the captains of teams I've invited to my challenge know about it?

There are two ways that World Community Grid informs captains about challenge invitations:

1. If a captain has chosen to receive Team E-mails (on the My Profile page), they will receive an email for each challenge to which they are invited.
2. On the My Team page, there is a Challenge Control Panel. Team captains will see challenges to which they've been invited under a section called Pending Challenges. Captains can accept challenges directly from the Challenge Control Panel, or they can click the name of the Team Challenge to view the full details of the Team Challenge before accepting or declining the invitation.

How do I create a Team Challenge?

As the captain of a team, you may create as many Team Challenges as you want; the only requirement is that they have different names so members can tell them apart from other Team Challenges.

To create a Team Challenge, go to My Contribution and click on My Team in the lefthand navigation. Just under the Team Information, you'll see the Team Control Panel with an Issue Team Challenge button. Click the button to be taken to the Issue Team Challenge page.

Once on the Issue Team Challenge page, you start by picking a name for your Team Challenge. After that, decide if you want your Team Challenge to be open to all teams, or if you want to choose which teams to invite. If you want an Open Challenge, check the box next to "Open Challenge?"

Next up, pick the dates for your Team Challenge. The Start Date must be at least one day in the future, but not more than 30 days away. The End Date must be at least one day after the Start Date, but not more than 180 days after the Start Date.

Once you've chosen the dates, select what type of Team Challenge you'd like. The choices are Points, Run Time, and Results Returned, or an Increase in one of Points, Run Time, or Results Returned. For more in the "increase" challenges, read this FAQ.

Next choose whether or not you want to allow Late Joiners; that is, allow teams to join the challenge after the Start Date. This applies to teams that are invited as well as for Open challenges. Teams that join a challenge after the Start Date will only receive credit for statistics after they join the challenge.

Last but not least, you may invite other teams to participate in your Team Challenge. You may invite teams even if your are issuing an Open Challenge. If you are issuing a Closed Challenge you must invite at least one team.

To invite teams, just search for the name of the team you want to invite, and click the link to "Invite This Team." For more general searches, only the first 25 teams are returned. If this happens, try being a little more specific in your search.

Plan Ahead for Team Challenges!

It's a good idea to make the Start Date of your Team Challenge at least a week in the future so that other teams will have a chance to join your challenge before it starts. Remember, after the Start Date, no teams may join your challenge, unless you opt to allow Late Joiners, so try to give the other team captains adequate time to get in!

How do I invite teams from my team's country?

Unfortunately, the Issue Team Challenge team search doesn't filter by country. To invite teams from your country to your Team Challenge, you can filter by country on the Find A Team page, and then do a search by name on the Issue Team Challenge search for the teams that come up in the country-filtered Find A Team search. The best way to do this is to open two browser windows so that you can have each page open at the same time. The Issue Team Challenge page will not save the teams you've invited if you go to a different page before clicking the submit button.

What is BEDAM and how has it been used in the past?

BEDAM stands for “Binding Energy Distribution Analysis Method”. It is a method developed by the Levy group which uses advanced sampling and analysis techniques to calculate absolute binding free energies based on a foundation in statistical mechanics and data generated from molecular dynamics simulations.

In a collaboration between the Olson group at The Scripps Research Institute and the Levy group at Temple University, BEDAM techniques were recently developed and used in a computational challenge (SAMPL4) demonstrating that docking coupled with subsequent BEDAM processing gives more reliable hits. This challenge used blind data from a pharmaceutical company working on HIV Integrase inhibitors. The AutoDock Vina/BEDAM modeling performed the best among all automated computational predictions submitted in the challenge.

How will the results of this project help other watersheds and catchments?

The Chesapeake Bay Watershed is but one of over 400 major watershed/catchment systems globally. It is not unique in facing the challenges of population growth, increasing urbanization, and the challenges of changing environmental conditions. The results to be reported from this project can inform policy-makers worldwide as to best practices to employ to restore and sustain the globe’s precious water resources. More importantly, perhaps, information from this simulation can help citizens make better choices and help the private sector identify opportunities for new products, services, and processes that reduce nutrient flow.

How will The Clean Energy Project help find solar cell materials?

Understanding the properties of new materials that are the basis of alternative sources of renewable energy represents one of today’s major scientific challenges. Many of these materials are composed of large organic molecules that contain hundreds of atoms. These atoms can be rearranged in multiple ways to fine-tune the properties of the desired material. With the aid of World Community Grid, researchers will evaluate the conductive properties of at least 1,000,000 molecular structures (created by combinatorial methods) that are suitable for organic solar cells applications. The results of such an enormous number of computations will be used to create a public database of molecular properties for data mining.

How will The Clean Energy Project help find solar cell materials?

Understanding the properties of new materials that are the basis of alternative sources of renewable energy represents one of today’s major scientific challenges. Many of these materials are composed of large organic molecules that contain hundreds of atoms. These atoms can be rearranged in multiple ways to fine-tune the properties of the desired material. With the aid of World Community Grid, researchers will evaluate the conductive properties of at least 100,000 molecular structures (created by combinatorial methods) that are suitable for organic solar cells applications. The results of such an enormous number of computations will be used to create a database of molecular properties for data mining, which will be publicly available.

Is there any way to estimate an end date for projects running on World Community Grid?

There are many variables with each project that determine how long it will last and how much work it will run on World Community Grid. These include:

• Change in research direction or project scope (e.g., results from work on World Community Grid that takes the project in a new direction)
• Increase or decrease in lab resources such as funding, staffing, etc
• New research findings from collaborators or other scientists in the same field 
• The pace at which computational work is being performed on World Community Grid

Researchers rarely know if or when these variables will come into play during their projects, which makes it challenging to estimate a project end date with any level of accuracy.

Does World Community Grid have a Twitter feed?

Yes, you can find World Community Grid on Twitter at: http://twitter.com/WCGrid

You can link World Community Grid to your Twitter account to automatically show your friends what you're doing to help solve the challenges facing our world. To do that, please click here.

For more information about Twitter, click here.

How does a molecular dynamics simulation work?

Newton wrote down simple equations of motion to describe how balls fly through the air or apples fall. The world of atoms and molecules is subject to quantum mechanics, which is a good deal more complex than classical Newtonian mechanics. Yet it turns out that by making certain approximations and simplifications, it is possible to simulate the molecular world by letting large numbers of atoms or molecules interact according to Newton’s laws.

So the idea of a molecular dynamics simulation is to let things evolve using a computer program which can track every detail of what happens to each molecule over time as it is buffeted by all the surrounding ones. But to get a statistically meaningful picture from such simulations it usually requires repeating the simulations thousands or even millions of times with slightly different starting conditions. It is this computational challenge that this project addresses, by getting volunteers to provide more than a thousand times the computing power that a typical research group would have access.

What treatments options exist today for TB?

The usual course of treatment for pulmonary TB is two antibiotics (isoniazid and rifampicin) every day for six months and two additional antibiotics (pyrazinamide and ethambutol) every day for the first two months. It may be several weeks or even months before the patient starts feeling better. Such long treatments cause implications such as increased relapse risk, serious side effects from the drugs (such as loss of appetite, nausea, dizziness, abdominal pain and blurred vision), increased risk of clinical hepatitis, especially in cases of underlying liver disease, and, crucially, treatment noncompliance. Additionally, there are strains of TB which are resistant to nearly all antibiotics used to treat TB. Patients with drug-resistant TB need to receive special medical treatment that can potentially cause more side effects, such as depression or psychosis, hearing loss, hepatitis, and kidney impairment. These patients will also be under greater risk of dying from the disease. Resistant TB treatment is extremely challenging as it is very expensive, lengthy and disruptive for the patients’ lives

How is Protinfo different from other approaches?

Protein structure prediction is an active area of research, and no one method or methodology is "best" for all situations. The public success of projects like Folding@Home, POEM@Home, Human Proteome Folding, and Rosetta@Home are evidence of the interest in solving this computationally challenging problem. We wish to offer another approach that differs in certain subtle but significant ways that can provide complementary and competitive results.

Some approaches (like Folding@Home and POEM@Home) simulate the protein folding process as we believe it occurs in real life, where physical energies are minimized. Protinfo (like Human Proteome Folding and Rosetta@Home) uses a minimization of "statistical energies" to identify likely protein structures, but with a slightly different approach. Rather than relying on a single complex energy function, Protinfo uses a simple, easily evaluated function and chooses the best structures by following up with a set of more sophisticated functions. Another difference is that Protinfo uses a novel continuous sampling methodology that enables us to explore good structures more finely. The continuous sampling methodology incurs little memory overhead and evaluating our compact energy function is very fast. This allows Protinfo to run on almost any computer.

The Protinfo structure predictions have been ranked as some of the best by the Critical Assessment of Structure Prediction (CASP) competition since 1994. You can read more about Protinfo on the researchers' page about this project.

Why is protein structure prediction so difficult?

Two factors that make protein structure prediction challenging are the nature of the energy functions, and the vast search space.

The environment of a protein is populated with many other atoms and molecules. If the program were simulating a process that happened in vacuo or even in a non-polar solvent (instead of the aqueous environment of the cytoplasm) it would be much easier. The presence of polar and polarizable solvent molecules make accurate calculation of electrostatic forces extremely difficult. In addition, the main "force" in protein folding is the hydrophobic effect. This arises from the interactions between atoms within the protein, their interactions with the solvent atoms and the interactions between the solvent atoms. In simulations such as Protinfo, Human Proteome Folding, and Rosetta@Home, the effect of these solvent dependent interactions is approximated in the statistical energies. The development of better solvent models and simulations is another active area of research that will eventually address these problems.

The other limiting factor is the number of possible structures, or conformations, that need to be sampled for a protein. Even with a completely accurate energy function, there is still a need to sample the possible conformations finely enough to find the right one. Not only is the number of possible conformations huge (see Levinthal paradox), it is made even more difficult by the extremely complicated energy landscape. Most of the usual global optimization techniques that could be used with a well behaved function will fail when applied to protein folding. Luckily, of the two problems, this is probably the lesser. With increased CPU power and improved sampling techniques generally some accurate structures are usually generated - but without the completely accurate energy function we are not always able to identify them.

HPF1 vs. HPF2: Solvation - modeling the protein in water at higher resolution

Another major challenge with high-resolution methods is the difficulty of computing accurate potentials for atomic-detail protein modeling in solvent; with electrostatic and solvation terms being among the most difficult terms to accurately model. Full treatment of the free energy of a protein conformation (with correct treatment of dielectric screening) is not a problem with an efficient solution and the computational cost of full treatment of electrostatic free energy (by solving the Poisson-Boltzmann or linearized Poisson-Boltzmann equations for large numbers of conformations) is high. In spite of these difficulties several studies have shown that refinement of de novo structures with atomic-detail potentials can increase our ability to select and or generate near native structures. These methods can correctly select near native conformations from these ensembles and improve near native structures, but still rely heavily on the initial low-resolution search to produce an ensemble containing good starting structures (HPF2 like methods rely on initial search with HPF1 like methods) (Lee et al. 2001; Misura and Baker 2005; Tsai et al. 2003). Some recent examples of high res predictions are quite encouraging, and an emerging consensus in the field is that higher resolution de novo structure prediction (structure predictions with atomic detail representations of side chains) will begin to work if sampling is dramatically increased (thus the grid!). The solvation score is depicted in one of the three score panels in the HPF2 client.

HPF1 vs. HPF2: Scoring different structures at higher resolutions

Balancing resolution with computational efficiency:
Protein structure prediction procedure must strike a delicate balance between the computational efficiency of the procedure and the level of physical detail used to model protein structure within the procedure. Low-resolution models can be used to predict protein topology/folds and sometimes suggest function (Bonneau et al. 2001b). Low-resolution models have also been remarkably successful at predicting features of the folding process such as folding rates and phi values (Alm and Baker 1999a; Alm and Baker 1999b). It is clear, however, that modeling proteins (and possibly bound water and other cofactors) at atomic detail, and scoring these higher resolution models with physically derived, detailed, potentials is a needed development if higher resolution structure prediction is to be achieved. Recent progress has focused on the use of low-resolution approaches for finding the fold followed by a refinement step where atomic detail is added (side chains added to the backbone) and physical scoring functions are used to select and/or generate higher resolution structures. Several recent studies have illustrated the usefulness of using de novo structure prediction methods as part of a two stage process in which low-resolution methods are used for fragment assembly and the resulting models are refined using a more physical potential and atomic detail (e.g. rotamers) to represent side chains (Bradley et al. 2003; Misura and Baker 2005; Tsai et al. 2003). In the first step Rosetta is used to search the space of possible backbone conformations with all side chains represented as centroids. This process is well described and has well characterized error rates and behavior. High confidence or low scoring models are then refined using potentials that account for atomic detail such as hydrogen bonding, van der Waals forces and electrostatics.
One major challenge that faces methods attempting to refine de novo methods is that the addition of side-chain degrees of freedom combined with the reduced length scale (reduced radius of convergence) of the potentials employed require the sampling of a much larger space of possible conformations. Thus, one has to correctly determine roughly twice the number of bond angles to a higher tolerance if one hopes to succeed.