Hubbry Logo
World Community GridWorld Community GridMain
Open search
World Community Grid
Community hub
World Community Grid
logo
8 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
World Community Grid
World Community Grid
World Community Grid
View on Wikipedia
from Wikipedia
World Community Grid
Developer(s)
Initial releaseNovember 16, 2004 (2004-11-16)[1]
Stable release7.16.19
Development statusActive
Operating system• Microsoft Windows
• Linux
• macOS
• Android
• Raspberry Pi OS
PlatformBOINC
TypeVolunteer computing
Average performance402 TFLOPS[2]
Active users23,248[2]
Total users79,354[2]
Active hosts57,672[2]
Total hosts5,517,865[2]
Websitewww.worldcommunitygrid.org or try https://www.cs.toronto.edu/~juris/jlab/wcg.html

World Community Grid (WCG) is an effort to create the world's largest volunteer computing platform to perform scientific research that benefits humanity.[3] Launched on November 16, 2004, with proprietary Grid MP client from United Devices and adding support for Berkeley Open Infrastructure for Network Computing (BOINC) in 2005, World Community Grid eventually discontinued the Grid MP client and consolidated on the BOINC platform in 2008.[4] In September 2021, it was announced that IBM transferred ownership to the Krembil Research Institute of University Health Network in Toronto, Ontario.[5]

World Community Grid uses unused processing power of consumer devices (PCs, Laptops, Android Smartphones, etc.) to analyse data created by the research groups that participate in the grid. WCG projects have analysed data related to the human genome, the human microbiome, HIV, dengue, muscular dystrophy, cancer, influenza, Ebola, Zika virus, virtual screening, rice crop yields, clean energy, water purification and COVID-19, among other research areas.[6]

There are currently five active projects and 28 completed projects.[7] Several of these projects have published peer-reviewed papers based on the analysis of the data generated by WCG. These include an OpenZika project paper on the discovery of a compound (FAM 3) that inhibits the NS3 Helicase protein of the Zika virus, thus reducing viral replication by up to 86%;[8][9] a FightAIDS@home paper on the discovery of new vulnerabilities on the HIV-1 Capsid protein which may allow for a new drug target;[10][11] and a FightAIDS@home paper on new computational drug discovery techniques for more refined and accurate results.[12][13]

History

[edit]

In 2003, IBM and other research participants sponsored the Smallpox Research Grid Project to accelerate the discovery of a cure for smallpox.[14] The smallpox study used a massive distributed computing grid to analyse compounds' effectiveness against smallpox.[15] The project allowed scientists to screen 35 million potential drug molecules against several smallpox proteins to identify good candidates for developing into smallpox treatments. In the first 72 hours, 100,000 results were returned. By the end of the project, 44 strong treatment candidates had been identified.[16] Based on the success of the Smallpox study, IBM announced the creation of World Community Grid on November 16, 2004, with the goal of creating a technical environment where other humanitarian research could be processed.[1][15]

World Community Grid initially only supported Windows, using the proprietary Grid MP software from United Devices which powered the grid.org distributed computing projects. Demand for Linux support led to the addition in November 2005 of open source Berkeley Open Infrastructure for Network Computing (BOINC) software which powers projects such as SETI@home and Climateprediction.[17] Mac OS and Linux support was added since the introduction of BOINC.[18] In 2007, the World Community Grid migrated from Grid MP to BOINC for all of its supported platforms.[19]

In September 2021, IBM announced that it had transferred ownership of the World Community Grid to the Krembil Research Institute.[20]

Scale of the project

[edit]

As of January 8, 2023, World Community Grid had over 23,000 active user accounts, with over 57,000 active devices.[2] Over the course of the project, more than 2,000,000 cumulative years of computing time have been donated, and over 6,000,000,000 work units have been completed.[21]

Operation

[edit]
The World Community Grid client software works in the background, showing itself as a small icon in the computer's system tray. When the BOINC client is used, as in this example, the icon is yellow and blue.
The client software's status window, displaying information about the work currently being done in the background. This particular computer is 95.6% complete with its current workunit. When it reaches 100%, it will start on a new workunit and the results of the previous workunit will be transmitted back to WCG.

The World Community Grid software uses the unused computing time of Internet-connected devices to perform research calculations.[22] Users install WCG client software onto their devices. This software works in the background, using spare system resources to process work for WCG.[22][23] When a piece of work or workunit is completed, the client software sends it back to WCG over the Internet and downloads a new workunit.[3][24] To ensure accuracy, the WCG servers send out multiple copies of each workunit.[25] Then, when the results are received, they are collected and validated against each other.[26]

World Community Grid offers multiple humanitarian projects under a single umbrella. Users are included in a subset of projects by default, but may opt out of projects as they choose.[27]

Even though WCG makes use of open source client software, the actual applications that perform the scientific calculations may not be. However, several of the science applications are available under a free license, although the source is not available directly from WCG.[28]

Potential problems

[edit]
The picture shows particular two CPU usage history (under Hyper-threading) when BOINC client software is processing two tasks on each CPU under Microsoft Windows XP SP2. CPU usage history indicates almost 0% to 100% swing with peak to peak of 3 seconds interval, when view +update speed set to high, at first half recording period. The rest of half period of history is set to update speed normal, and upper CPU usage history indicates slightly more than 60% and lower CPU usage history show 35% approx. in average.

The World Community Grid software increases CPU usage by consuming unused processing time; in the late 1990s and early 2000s, such calculations were meant to reduce "wasted" CPU cycles.[29] With modern CPUs, where dynamic frequency scaling is prevalent, increased usage makes the processor run at higher frequency,[30] increasing power usage and heating counter to power management. Additionally, because of an increasing focus on power performance,[31] or performance per watt, connecting old/inefficient computers to the grid will increase the total/average power required to complete the same calculations.

The BOINC client avoids slowing the computer by using a variety of limits that suspend computation when there are insufficient free resources. Unlike other BOINC projects, World Community Grid set the BOINC defaults conservatively, making the chances of computer damage extremely small. The default CPU throttle is 60%. The throttle is coarse-grained; for example, if usage is set to 60% it will work at 100% for 3 seconds, then at 0% for 2 seconds, resulting in an average decrease of processor use.[32]

An add-on program for Windows computers – TThrottle – can solve the problem of overheating by directly limiting the BOINC project's use of the host computer. It does this by measuring the CPU and/or the GPU temperature and adjusts the run time accordingly. It also uses a shorter switching time of less than one second, resulting in less temperature change during switching.[citation needed]

Statistics and competition

[edit]

The contributions of each user are recorded and user contribution statistics are publicly available.[21] Due to the fact that the processing time of each workunit varies from computer to computer, depending on the difficulty of the workunit, the speed of the computer, and the amount of idle resources available, contributions are usually measured in terms of points. Points are awarded for each workunit depending on the effort required to process it.[33]

Upon completing a workunit, the BOINC client will request the number of points it thinks it deserves based on software benchmarks (see BOINC Credit System#Cobblestones). Since multiple computers process the same workunit to ensure accuracy, the World Community Grid servers can look at the points claimed by each of those computers. The WCG servers disregard statistical outliers, average the remaining values and award the resulting number of points to each computer.[34][35]

Within the grid, users may join teams that have been created by organizations, groups, or individuals. Teams allow for a heightened sense of community identity and can also inspire competition. As teams compete against each other, more work is done for the grid overall.[36]

Outreach

[edit]

World Community Grid recognizes companies and organizations as partners if they promote WCG within their company or organization. As of April 2021, WCG had 452 partners.[37]

Also, as part of its commitment to improving human health and welfare, the results of all computations completed on World Community Grid are released into the public domain and made available to the scientific community.[3]

Scientific results

[edit]

Since its launch, more than thirty projects have run in the World Community Grid. Some of the results include:

  • In February 2014, the Help Fight Childhood Cancer project scientists announced the discovery of 7 compounds that destroy neuroblastoma cancer cells without any apparent side effects.[38] This discovery, made with the support of the WCG volunteers, is a positive step towards a new treatment. The project has announced that it is seeking a collaboration with a pharmaceutical company in order to develop the compounds into treatments. Given the success of the project, the scientists have stated that they are already planning a follow-up project which will focus on other pediatric cancers, possibly in collaboration with a newly formed Pan-Asian oncology group, of which they are a founding member.[39]
  • As of July 2012, the Human Proteome Folding Project has published several papers using data from WCG.[40] These include a paper on validation methods and a new database of protein structure and function predictions;[41] a paper on the identification of proteins that regulate human processes;[42] a paper on the analysis of the genomes from five plant families and their proteomes, for which WCG was used in the creation of over 29,000 protein structures;[43] a paper on the proteome of Saccharomyces cerevisiae.[44]
  • The GO Fight Against Malaria project reported the discovery of several molecules that are effective against Malaria and Drug-Resistant Tuberculosis (including TDR-TB, for which there is no treatment available). The project also tested for new molecules against MRSA, Filariasis and Bubonic Plague. Laboratory testing continues in order to turn those molecules into possible treatments. GFAM was also the first project ever to perform a billion different docking calculations.[45] A paper was published in January 2015,[46][47] with two more pending submission. In June 2015, the project reported that of the two "hits" discovered against a drug-resistant tuberculosis strain, several "analogs" have been synthesized, the best one of which inhibits the growth of Mycobacterium tuberculosis and is relatively non-toxic to mammalian cells.[46] Lack of funding prevented further research into the data.
  • The Discovering Dengue Drugs - Together project scientists reported the discovery of several new Dengue protease inhibitors, most of which also inhibit the West Nile virus protease. A handful of these have already entered "crucial pre-clinical pharmacokinetic and efficacy studies". In November 2014, an update reported that the scientists have a drug lead that disables a key enzyme that allows the Dengue virus to replicate. It has also shown the same behaviour in other flaviviruses, such as the West Nile virus. No negative side effects such as toxicity, carcinogenicity or mutagenicity have been observed, making this drug lead a very strong antiviral drug candidate for these viruses. The scientists are now working to synthesize variants of the molecule to improve its activity and enter planned pre-clinical and clinical trials.[48] However, in an October 2018 update, the research team reported that none of their current designs had produced a highly potent dengue protease inhibitor that could be tested in vivo.[49]
  • In June 2013, the Clean Energy Project published a database of over 2.3 million organic molecules which have had their properties characterized. Of these, 35,000 molecules have shown the potential to double the efficiency over organic solar cells currently being produced. Before this initiative, scientists knew of just a handful of carbon-based materials that were able to convert sunlight into electricity efficiently.[50][51]
  • In February 2010, the FightAIDS@Home project scientists announced that they have found two compounds which make a potentially new class of AIDS-fighting drugs possible. The compounds attach to the virus at newly discovered binding sites, and thus can be used to "enhance existing therapies, treat drug-resistant strains of the disease, and slow the evolution of drug resistance in the virus."[52][53]
  • In July 2015, the Drug Search for Leishmaniasis project announced it had tested the top 10 compounds with highest predicted efficiency out of over 100 identified via WCG workunits. Of those 10, 4 showed "positive results" in in vitro testing, with one showing "an exceptionally promising result".[54] In August 2017, in vivo testing of the 4 compounds on hamsters showed favourable results, with one compound inducing "an almost complete curing of the lesions in two out of five hamsters."[55] However, in a March 2018 update, the research team announced none of the 10 tested compounds had sufficient anti-leishmaniasis activity.[56]
  • In July 2015, the Computing for Clean Water project announced that a paper had been published in the Nature Nanotechnology journal describing a new type of water filter efficiently utilising nanotubes. "[The] nanotubes are made of single-atom-thick sheets of carbon atoms, called graphene, rolled up into tiny tubes, with diameters of just a few nanometers - one ten-thousandth the diameter of a human hair. The size of the tubes allows water molecules to pass through, but blocks larger pathogens and contaminants, purifying the water." By running simulations on WCG, the scientists discovered that certain kinds of natural vibrations called phonons, under specific conditions, can lead to more than 300% increased flow of water through the nanotubes, compared to previous theoretical predictions.[57]
  • In April 2015, the Say No To Schistosoma project scientists reported that subsequent analysis had been performed, and the three most promising candidate substances had been identified for in vitro testing.[58]
  • In March 2019, FightAIDS@Home researchers published a paper describing a "Novel Intersubunit Interaction Critical for HIV-1 Core Assembly" that "defines a Potentially Targetable Inhibitor Binding Pocket". Using World Community Grid, more than 1.6 million compounds were used to target 20 conformations of this pocket. Preliminary results suggest it to be a plausible binding site for antiviral compounds. Further analysis of these compounds are the subject of an independent study.[59]

Active subprojects

[edit]

OpenPandemics - COVID-19

[edit]

On April 1, 2020, IBM announced OpenPandemics - COVID-19. The project aims to identify possible treatments for the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which is responsible for the COVID-19 pandemic. WCG will partner with Scripps Research, with whom it has partnered in the past, notably in FightAIDS@Home projects. The project runs on CPUs and GPUs and will also serve to create a "fast-response, open source tool that will help all scientists quickly search for treatments for future pandemics."[6][60][61][62]

The project launched on May 14, 2020.[63]

Mapping Cancer Markers

[edit]

Mapping Cancer Markers (launched November 8, 2013). The project aims to identify the markers associated with various types of cancer, and is analyzing millions of data points collected from thousands of healthy and cancerous patient tissue samples. These include tissues with lung, ovarian, prostate, pancreatic and breast cancers. By comparing these different data points, researchers aim to identify patterns of markers for different cancers and correlate them with different outcomes, including responsiveness to various treatment options. The project is focusing on 4 types of cancer, with the first focus being on lung cancer, and will move on to ovarian cancer, prostate cancer and sarcoma.[64][65]

Africa Rainfall Project

[edit]

The Africa Rainfall Project (launched October 2019) will use the computing power of World Community Grid, data from The Weather Company, and other data to improve rainfall modelling, which can help farmers in sub-Saharan Africa successfully raise their crops.[66] The amount of RAM that can be involved in calculations is from 1 to 16 gigabytes.[67]

Completed subprojects

[edit]

Human Proteome Folding – Phase 1

[edit]
Main article: Human Proteome Folding Project

The first project launched on World Community Grid was the Human Proteome Folding Project, or HPF1, which aims to predict the structure of human proteins. The project was launched on November 16, 2004,[68] and completed on July 18, 2006.[68] This project was unique in that computation was done in tandem with the grid.org distributed computing project.[69] Devised by Richard Bonneau at the Institute for Systems Biology, the project used grid computing to produce the likely structures for each of the proteins using a Rosetta Score. From these predictions, researchers hope to predict the function of the myriad proteins. This increased understanding of the human proteins could prove vital in the search for cures to human diseases.[70] Computing for this project was officially completed on July 18, 2006.[71] Research results for the yeast portion of HPF1 have been published.[72]

Human Proteome Folding – Phase 2

[edit]
Main article: Human Proteome Folding Project

Human Proteome Folding - Phase 2 (HPF2) (launched June 23, 2006[73]) was the third project to run on World Community Grid, and completed in 2013. This project, following on from HPF1, focused on human-secreted proteins, with special focus on biomarkers and the proteins on the surface of cells as well as Plasmodium, the organism that causes malaria. HPF2 generates higher-resolution protein models than HPF1. Though these higher-resolution models are more useful, they also require more processing power to generate.[74]

In a July 2012 status report, the project scientists reported that the results generated by the WCG calculations are being used by Dr. Markus Landthaler of the Max Delbruch Center for Molecular Medicine (MDC) in Berlin. The HPF2 results helped Dr. Markus Landthaler and his collaborators in writing up a new paper on "The mRNA-Bound Proteome and Its Global Occupancy Profile on Protein-Coding Transcripts"[75]

Help Defeat Cancer

[edit]
Main article: Help Defeat Cancer

The Help Defeat Cancer project seeks to improve the ability of medical professionals to determine the best treatment options for patients with breast, head, or neck cancer. The project was launched on July 20, 2006,[68] and completed in April 2007.[68] The project worked by identifying visual patterns in large numbers of tissue microarrays taken from archived tissue samples. By correlating the pattern data with information about treatment and patient outcome, the results of this project could help provide better targeted treatment options.[76]

Genome Comparison

[edit]
Main article: Fiocruz Genome Comparison Project

The Genome Comparison project is sponsored by the Brazilian research institution Fiocruz.[73] The project was launched on November 21, 2006,[68] and completed on July 21, 2007.[68] The project seeks to compare gene sequences of different organisms against each other in order to find similarities between them. Scientists hope to discover what purpose a particular gene sequence serves in a particular function of one organism, via comparing it to a similar gene sequence of known function in another organism.[77]

Help Cure Muscular Dystrophy – Phase 1

[edit]
Main article: Help Cure Muscular Dystrophy

Help Cure Muscular Dystrophy is run by Décrypthon, a collaboration between French Muscular Dystrophy Association, French National Center for Scientific Research and IBM. Phase 1 was launched on December 19, 2006,[73] and completed on June 11, 2007.[78] The project investigated protein–protein interactions for 40,000 proteins whose structures are known, with particular focus on those proteins that play a role in neuromuscular diseases. The database of information produced will help researchers design molecules to inhibit or enhance binding of particular macromolecules, hopefully leading to better treatments for muscular dystrophy and other neuromuscular diseases.[79] This project was available only to agents running the Grid MP client, making it unavailable to users running BOINC.[80]

Discovering Dengue Drugs – Together

[edit]
Main article: Discovering Dengue Drugs – Together

Discovering Dengue Drugs – Together was sponsored by scientists at the University of Texas and the University of Chicago and will run in two phases.[81] Phase 1, launched August 21, 2007,[73] used AutoDock 2007 (the same software used for FightAIDS@Home) to test potential antiviral drugs (through NS3 protease inhibition) against viruses from the family flaviviridae and completed on August 11, 2009.[82][83] Phase 2 "[uses] a more computationally intensive program to screen the candidates that make it through Phase 1."[84] The drug candidates that make it through Phase 2 will then be lab-tested.[84]

AfricanClimate@Home

[edit]

The mission of AfricanClimate@Home was to develop more accurate climate models of specific regions in Africa. It was intended to serve as a basis for understanding how the climate will change in the future so that measures designed to alleviate the adverse effects of climate change could be implemented. World Community Grid's tremendous computing power was used to understand and reduce the uncertainty with which climate processes were simulated over Africa. Phase 1 of African Climate@Home launched on September 3, 2007,[85] and ended in July 2008.[86]

Help Conquer Cancer

[edit]
Main article: Help Conquer Cancer

Help Conquer Cancer project (launched November 1, 2007[87]) is sponsored by the Ontario Cancer Institute (OCI), Princess Margaret Hospital and University Health Network of Toronto, Canada. The project involves X-ray crystallography. The mission of Help Conquer Cancer is to improve the results of protein X-ray crystallography, which helps researchers not only annotate unknown parts of the human proteome, but importantly improves their understanding of cancer initiation, progression and treatment.[88]

The HCC project was the first WCG project benefiting from graphics processing units (GPU)s which helped finish it a lot earlier than initially projected due to the massive power of GPUs. In the April 2013 status report[89] the scientists report there is still a lot of data to analyze but that they are preparing a new project that will search for prognostic and predictive signatures (sets of genes, proteins, microRNAs, etc.) that help predict patient survival and response to treatment. The project finished in May 2013.[citation needed]

Nutritious Rice for the World

[edit]
Main article: Nutritious Rice for the World

The Nutritious Rice for the World project is carried out by Ram Samudrala's Computational Biology Research Group Archived 2008-06-14 at the Wayback Machine at the University of Washington. The project was launched on May 12, 2008, and completed on April 6, 2010.[90] The purpose of this project is to predict the structure of proteins of major strains of rice, in order to help farmers breed better rice strains with higher crop yields, promote greater disease and pest resistance, and utilize a full range of bioavailable nutrients that can benefit people around the world, especially in regions where malnutrition is a critical concern. The project has been covered by more than 200 media outlets since its inception.[91] On April 13, 2010, World Community Grid officially announced that the Nutritious Rice for the World project finished on April 6, 2010.[90]

In April 2014, an update was posted stating that the research team was able to publish structural information about thousands of proteins, and advance the field of computational protein modeling. These results – which were only possible because of the massive amount of donated computing power they had available – are expected to guide future research and plant science efforts.[92]

The Clean Energy Project

[edit]
Main article: Clean Energy Project

The Clean Energy project is sponsored by the scientists of Harvard University's Department of Chemistry and Chemical Biology.[93] The mission of the Clean Energy Project is to find new materials for the next generation of solar cells and later, energy storage devices. Researchers are employing molecular mechanics and electronic structure calculations to predict the optical and transport properties of molecules that could become the next generation of solar cell materials.[citation needed]

Phase 1 was launched on December 5, 2008, and completed on October 13, 2009.[94] By harnessing the computing power of the World Community Grid, researchers were able to calculate the electronic properties of tens of thousands of organic materials – many more than could ever be tested in a lab – and determine which candidates are most promising for developing affordable solar energy technology.[95]

Phase 2 was launched June 28, 2010,[96] sponsored by the scientists of Harvard University's Department of Chemistry and Chemical Biology.[93] Further calculations about optical, electronic and other physical properties of the candidate materials are being conducted with the Q-Chem quantum chemistry software.[97] Their findings have been submitted to the Energy & Environmental Science journal.[98]

Help Fight Childhood Cancer

[edit]

Help Fight Childhood Cancer project (launched March 13, 2009[99]) is sponsored by the scientists at Chiba Cancer Center Research Institute and Chiba University.[100] The mission of the Help Fight Childhood Cancer project is to find drugs that can disable three particular proteins associated with neuroblastoma, one of the most frequently occurring solid tumors in children. Identifying these drugs could potentially make the disease much more curable when combined with chemotherapy treatment.[101]

[edit]
Main article: Influenza Antiviral Drug Search

Influenza Antiviral Drug Search project is sponsored by Dr. Stan Watowich and his research team at The University of Texas Medical Branch (Galveston, Texas, USA).[102] The project was launched on May 5, 2009, and completed on October 22, 2009.[103] The mission of the Influenza Antiviral Drug Search project is to find new drugs that can stop the spread of an influenza infection in the body. The research will specifically address the influenza strains that have become drug resistant as well as new strains that are appearing. Identifying the chemical compounds that are the best candidates will accelerate the efforts to develop treatments that would be useful in managing seasonal influenza outbreaks, and future influenza epidemics and even pandemics.[104] Phase 1 of The Influenza Antiviral Drug Search project has already finished on October 22, 2009. Now the researchers are performing post-processing on the results from Phase 1 and are preparing for Phase 2.[103]

In November 2012, the project's scientists stated that, given the fact that there is no immediate danger of an influenza outbreak, all of the project's results would be posted online and their resources would be refocused on the Dengue Project.[105]

Help Cure Muscular Dystrophy – Phase 2

[edit]
Main article: Help Cure Muscular Dystrophy

World Community Grid and researchers supported by Decrypthon, a partnership between AFM (French Muscular Dystrophy Association), CNRS (French National Center for Scientific Research), Universite Pierre et Marie Curie, and IBM were investigating protein–protein interactions for more than 2,200 proteins whose structures are known, with particular focus on those proteins that play a role in neuromuscular diseases. Phase 2 was launched on May 12, 2009,[106] and completed on September 26, 2012. The database of information produced will help researchers design molecules to inhibit or enhance binding of particular macromolecules, hopefully leading to better treatments for muscular dystrophy and other neuromuscular diseases.[107]

Phase 2 of the Help Cure Muscular Dystrophy project began once the results from the first phase had been analyzed. Phase 2 ran on the BOINC platform.[4][108]

Discovering Dengue Drugs – Together – Phase 2

[edit]
Main article: Discovering Dengue Drugs - Together

Discovering Dengue Drugs – Together – Phase 2 (launched February 17, 2010[109]) is sponsored by The University of Texas Medical Branch (UTMB) in Galveston, Texas, United States and the University of Chicago in Illinois, USA. The mission is to identify promising drug candidates to combat the Dengue, Hepatitis C, West Nile, Yellow Fever, and other related viruses. The extensive computing power of World Community Grid will be used to complete the structure-based drug discovery calculations required to identify these drug candidates.[110]

Computing for Clean Water

[edit]

Computing for Clean Water (launched September 20, 2010[111][112]) is sponsored by the Center for Nano and Micro Mechanics of Tsinghua University in Beijing. The project's mission is to provide deeper insight on the molecular scale into the origins of the efficient flow of water through a novel class of filter materials. This insight will in turn guide future development of low-cost and more efficient water filters. It is estimated that 1.2 billion people lack access to safe drinking water, and 2.6 billion have little or no sanitation. As a result, millions of people die annually – an estimated 3,900 children a day due to a lack of clean water.[113] On April 25, 2014, the project scientists released an update stating that they had exciting results to report when the paper is submitted and that the project on WCG was finished.[114]

Drug Search for Leishmaniasis

[edit]

Drug Search for Leishmaniasis (launched September 7, 2011[115]) is spearheaded by the University of Antioquia in Medellín, Colombia, with assistance from researchers at the University of Texas Medical Branch in Galveston, Texas. The mission is to identify potential molecule candidates that could possibly be developed into treatments for Leishmaniasis. The extensive computing power of World Community Grid will be used to perform computer simulations of the interactions between millions of chemical compounds and certain target proteins. This will help find the most promising compounds that may lead to effective treatments for the disease.[116]

GO Fight Against Malaria Project

[edit]

The mission of the GO Fight Against Malaria project (launched November 16, 2011[117]) is to discover promising drug candidates that could be developed into new drugs that cure drug resistant forms of malaria. The computing power of World Community Grid will be used to perform computer simulations of the interactions between millions of chemical compounds and certain target proteins, to predict their ability to eliminate malaria. The best compounds will be tested by scientists at The Scripps Research Institute in La Jolla, California, U.S.A. and further developed into possible treatments for the disease.[118]

Say No to Schistosoma

[edit]

Say No to Schistosoma (launched February 22, 2012[119]) was the 20th research project to be launched on World Community Grid. The researchers at Infórium University in Belo Horizonte and FIOCRUZ-Minas, Brazil, ran this project on World Community Grid to perform computer simulations of the interactions between millions of chemical compounds and certain target proteins in the hope of finding effective treatments for schistosomiasis.[120] As of April 2015, subsequent analysis had been performed, and three of the most promising candidate substances had been identified for in-vitro testing.[58]

Computing for Sustainable Water

[edit]

Computing for Sustainable Water was the 21st research project to be launched on World Community Grid. The researchers at the University of Virginia were running this project on World Community Grid to study the effects of human activity on a large watershed and gain deeper insights into what actions can support the restoration, health and sustainability of this important water resource.[121] The project was launched on April 17, 2012,[122] and completed on October 17, 2012.

Uncovering Genome Mysteries

[edit]

The Uncovering Genome Mysteries project launched on October 16, 2014, and is a joint collaboration between Australian and Brazilian scientists. The project aims to examine close to 200 million genes from many life forms and compare them with known genes in order to find out what their function is. The results could have an effect in fields such as medicine and environmental research.[123]

Outsmart Ebola Together

[edit]

Outsmart Ebola Together was a collaboration with the Scripps Research Institute to help find chemical compounds to fight Ebola virus disease.[124] It was launched on 3 December 2014.[125] The aim is to block crucial steps in the life cycle of the virus, by finding drugs with high binding affinity with certain of its proteins. There are two targets: a surface protein used by the virus to infect human cells, and "transformer" proteins which change shape to carry out different functions.[126] The project officially completed December 6, 2018.[127]

OpenZika

[edit]

OpenZika was launched on May 18, 2016, to help combat the Zika virus. The project targets proteins that are believed to be used by the Zika virus to survive and spread in the body, based on known results from similar diseases like dengue fever and yellow fever. These results will help researchers develop an anti-Zika drug.[128] The project officially completed December 13, 2019.[129]

FightAIDS@Home

[edit]
Main article: FightAIDS@Home

FightAIDS@Home (launched November 19, 2005[130]) was World Community Grid's second project and its first to target a single disease. Each individual computer processes one potential drug molecule and tests how well it would dock with HIV protease, acting as a protease inhibitor.[131] Scripps Research Institute published its first peer-reviewed scientific paper about the results of FightAIDS@Home on April 21, 2007.[132] This paper explains that the results up to that point will primarily be used to improve the efficiency of future FightAIDS@Home calculations.[133]

FightAIDS@Home Phase 2

[edit]

FightAIDS@Home Phase 2 (launched September 30, 2015[134]) is looking more closely at the results of Phase 1. The project has two goals in the early experiments; the simulation architecture is functioning correctly and giving reliable results, and using BEDAM and AutoDock together provides better results than using just BEDAM or AutoDock.[135]

Microbiome Immunity Project

[edit]

Microbiome Immunity Project (launched August 2017) is a study of proteins in bacteria located in and on the human body; the human microbiome, which comprises around 3 million separate bacterial genes. By studying bacterial genes, researchers can determine their individual shapes, which in turn dictate the function of the bacteria.[136] Collaborative institutions includes the University of California San Diego, Broad Institute of MIT and Harvard, and the Simons Foundation's Flatiron Institute.[137]

Help Stop TB

[edit]

Help Stop TB was launched in March 2016 to help combat tuberculosis, a disease caused by a bacterium that is evolving resistance to currently available treatments. The computations of this project target mycolic acids in the bacterium's protective coat, simulating the behaviour of these molecules to better understand how they offer protection to the bacteria.[138]

Smash Childhood Cancer

[edit]
Main article: Smash Childhood Cancer

Launched in January 2017, the Smash Childhood Cancer project builds on the work from the Help Fight Childhood Cancer project by looking for drug candidates targeting additional childhood cancers.[139][140] Upon Dr. Akira Nakagawara's retirement in March 2020, the principal investigator changed to Dr. Godfrey Chan, who was one of the original members of the Smash Childhood Cancer team. Additionally, PRDM14 and Fox01 have been added as new targets for investigation.[141] An inhibitor of the osteopontin protein was modeled.[142]

See also

[edit]

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

World Community Grid

View on Grokipedia
from Grokipedia
World Community Grid (WCG) is a global initiative that enables individuals to donate the spare processing power of their computers, smartphones, and other devices to advance scientific research on pressing humanitarian issues, such as treatment, modeling, and . Launched on November 16, 2004, by as part of its efforts, WCG pioneered the use of to tackle complex problems that would otherwise require massive supercomputing resources, allowing researchers to perform large-scale simulations and data analyses without significant financial barriers. As of 2025, following its 20th anniversary in 2024, the platform has grown to include over 818,000 volunteers contributing from more than 7.7 million devices, collectively donating the equivalent of 2.6 million years of computing power to support projects. Originally hosted and funded by , which provided technical infrastructure and expertise drawn from its long history of scientific collaboration, WCG transitioned its operations to the Krembil Research Institute in in 2021 to ensure continued sustainability and expansion of its humanitarian focus. The project operates on the Berkeley Open Infrastructure for Network Computing (BOINC) platform, where volunteers install free, secure software that runs tasks during idle times, ensuring no interference with device performance, battery life, or data usage. Key achievements include enabling breakthroughs in areas like cancer marker mapping, drug discovery through the OpenPandemics project, and improved rainfall forecasting for African agriculture via the Crucial Data, Better Crops initiative, all of which have accelerated discoveries previously deemed computationally infeasible. As of November 2025, WCG remains actively operational under Krembil's stewardship, with ongoing projects addressing genetics, pandemics, and environmental challenges, while periodically undergoing maintenance and cloud migrations to enhance efficiency.

Overview

Purpose and Founding Organization

World Community Grid is a non-profit volunteer computing project that harnesses the idle processing power of donated personal devices to support humanitarian scientific research addressing global challenges in areas such as , , and alleviation. By aggregating this capacity, the initiative enables researchers to perform large-scale simulations and data analyses that would otherwise be infeasible due to resource constraints. Founded in November 2004 by as part of its efforts, World Community Grid was established to create a global grid for dedicated to public-benefit research. provided the foundational infrastructure, including donated hardware, software, and technical expertise, without any commercial objectives, positioning the project as a philanthropic endeavor to advance societal good. The project emphasizes open-source collaboration with academic institutions, research organizations, and scientists worldwide, fostering partnerships that drive impactful discoveries in humanitarian fields. From its inception, it has integrated the BOINC (Berkeley Open Infrastructure for Network Computing) platform to facilitate secure and efficient task distribution to volunteers' devices. This model ensures that computational contributions remain focused on non-commercial, open-access research outcomes.

Scale and Global Participation

World Community Grid has attained substantial scale, engaging a vast network of volunteers worldwide. As of November 2025, over 818,000 individuals have participated, registering more than 7.7 million devices and collectively donating more than 2.68 million years of computing power to support scientific research. Participation spans 226 countries, reflecting broad global involvement. While volunteers are distributed across all regions, several countries in Europe and Asia each count thousands of contributors, underscoring concentrated engagement in these areas alongside widespread adoption elsewhere. Volunteers contribute through diverse devices, primarily desktops and laptops running the BOINC software, as well as Android smartphones and tablets via a dedicated app. Although the default configuration utilizes CPU resources, GPU support is available for certain projects when users enable it in their device profiles, allowing for enhanced computational efficiency on compatible hardware. The project's growth has been steady, with annual increases in completed tasks driven by expanding volunteer bases and device registrations. Notable surges occurred during global crises, such as the , when the OpenPandemics initiative attracted hundreds of thousands of new participants to accelerate efforts against SARS-CoV-2.

History

Inception and Early Years (2004–2007)

World Community Grid was launched on November 16, 2004, by as a philanthropic initiative aimed at mobilizing idle computing power from volunteers worldwide to support humanitarian scientific research. The project emerged from the success of IBM's earlier Research Grid, which had engaged over 2 million computers to screen potential treatments for the disease, delivering results to the U.S. Department of Defense. At launch, collaborated with leading institutions including the , , and to identify pressing global challenges in health and human welfare. The initial infrastructure utilized the proprietary Grid MP software developed by United Devices, which powered the grid.org platform and limited participation to Windows-based personal computers. This setup enabled the debut of the first project, the Human Proteome Folding Project, sponsored by the Institute for Systems Biology, which sought to predict the three-dimensional structures of human proteins to advance understanding of diseases like cancer and Alzheimer's. Phase 1 of the project ran from November 2004 to July 2006, generating a database of structures for approximately 120,000 protein domains using volunteer contributions equivalent to thousands of years of computing time. Early partnerships with academic institutions, such as the Institute for Systems Biology, were crucial for defining research priorities and validating computational outputs. Building the volunteer base presented significant initial challenges, including raising awareness of the platform and overcoming the barriers of that excluded non-Windows users. addressed these by launching promotional campaigns and securing endorsements from organizations like the U.S. Tennis Association and science centers, which helped attract early adopters. Despite these hurdles, the project experienced rapid growth, signing up 25,000 volunteers in its first week and reaching over 100,000 participants by 2006 through grassroots outreach and media coverage. In 2007, World Community Grid integrated with the open-source BOINC platform, expanding compatibility to and macOS systems and facilitating broader global participation while maintaining its focus on scalable .

Growth, Milestones, and Recent Developments (2008–2025)

Following its early years, World Community Grid experienced significant growth in participant engagement and computational capacity. By 2012, the platform had surpassed 2 million participating computers contributed by approximately 600,000 volunteers across 80 countries, marking a key expansion in global reach. In 2013, the introduction of an Android application broadened accessibility, allowing mobile devices to contribute idle computing power and further diversifying volunteer participation. This period also saw the platform handling increased workloads, such as reaching 400 million results returned by March 2010 and accelerating to over 1 million results per day by 2012. The project navigated global crises effectively, particularly during the , where the OpenPandemics initiative drew strong volunteer support, becoming one of the most backed efforts in WCG's history alongside projects on cancer and AIDS. In 2021, transferred operational management to the Krembil Research Institute at the in , enhancing academic leadership while preserving IBM's ongoing technical and financial backing. By 2022, cumulative volunteer contributions exceeded 806,000 unique members and 2.4 million years of computing time, demonstrating sustained scaling. Recent milestones include the celebration of WCG's 20th anniversary in November 2024, highlighting two decades of harnessing volunteer resources for humanitarian science. An extended downtime from December 7, 2024, to January 3, 2025, facilitated critical system updates, after which operations resumed, enabling the Africa Rainfall Project (ARP) to restart in early 2025. The ARP saw further progress with research updates in July 2025, where volunteers had generated key simulation data for rainfall forecasting in sub-Saharan Africa by July 7. In August 2025, following the decommissioning of the Graham cloud infrastructure, WCG fully migrated to the Nibi cloud on August 31, ensuring continued reliability amid evolving computational needs; a brief downtime of 2 hours occurred during this transition. By November 2025, total volunteers had grown to over 818,000, with more than 7.7 million devices registered historically.

Operation

Volunteer Computing Model

The World Community Grid employs a distributed model that leverages the BOINC (Berkeley Open Infrastructure for Network Computing) platform to harness idle computing resources from participants' devices worldwide. In this model, complex scientific computations, such as simulations, are divided into small, independent work units by researchers. These units are queued on central servers and distributed to volunteer devices only when the devices are idle and connected to the , ensuring minimal interference with users' primary activities. The workflow begins with volunteers installing the BOINC client software, which periodically contacts the World Community Grid servers to request available work units. Upon download, the device processes the unit using available resources, including CPU cycles, GPU processing where supported, and temporary storage for data files typically ranging from 100 MB to 1.5 GB. Once computation completes, results are uploaded back to the servers during the next connection. To ensure reliability and accuracy, the system uses redundancy validation: each is assigned to multiple volunteer devices (typically two or more), and results are compared; only matching outcomes are accepted as valid, discarding discrepancies caused by errors or malfunctions. Efficiency is maintained through adaptive scheduling mechanisms that prefetch work units—caching up to several days' worth—to allow offline processing without halting progress. The BOINC client automatically pauses or suspends tasks when the device is in use, running on battery power, or under high load, resuming seamlessly when conditions improve to prioritize while maximizing overall throughput. This non-intrusive approach supports diverse devices, including personal computers and Android mobiles, without requiring manual intervention from volunteers.

Software, Devices, and Integration

The primary software for participating in World Community Grid is a customized version of the BOINC (Berkeley Open Infrastructure for Network Computing) client, an open-source platform developed by the University of California, Berkeley. Volunteers download this pre-configured BOINC installer directly from the official World Community Grid website, which simplifies setup by automatically attaching the client to the grid upon installation. The software runs in the background, utilizing idle computing resources to process scientific tasks, and supports manual updates via the BOINC Manager interface or by downloading newer versions from the site to ensure compatibility with evolving projects. World Community Grid supports a range of devices to maximize volunteer participation. Desktop and laptop computers running or later (including x86 and architectures), macOS (64-bit only), and (x86, , and ARM variants) are fully compatible, enabling GPU acceleration for certain tasks where applicable. Mobile support includes Android devices running version 4.4 (KitKat) or higher, introduced in 2012 to harness processing power, though compatibility varies by device and requires at least 100 MB of storage plus project-specific requirements. iOS devices face limitations due to Apple's policies restricting background applications, resulting in no official full or direct integration for iOS participation. Integration emphasizes ease of onboarding for volunteers. The installation process features a one-click setup where users and run the , which prompts attachment to World Community Grid without manual configuration. Account creation occurs via email registration on the World Community Grid during or after installation, allowing immediate access to the platform. Once registered, users can join teams—communities of contributors competing on total computing power donated—to foster engagement and motivation. User controls provide flexibility to tailor participation. Through the BOINC Manager or web-based preferences dashboard, volunteers select specific research projects to support, set limits on power usage (such as running only when idle, on , or below certain battery thresholds on Android), and manage data sharing for public statistics and badges. These options ensure minimal impact on device performance while allowing contributors to monitor and adjust their computing contributions in real time.

Challenges and Mitigations

One of the primary operational challenges in World Community Grid (WCG) arises from network downtime, which can interrupt the transmission of incomplete computational tasks between volunteer devices and central servers, leading to delays in progress. Device heterogeneity, encompassing varied hardware like and processors alongside diverse operating systems (predominantly Windows but including Mac and ), often results in computation errors or incompatibilities during task execution. Additionally, volunteer churn—characterized by the sporadic availability of devices as participants join or depart—exacerbates unreliability, as resources are not dedicated and can vanish unpredictably. To address security concerns, WCG ensures no is processed or accessed by volunteer devices, with the software client limited to handling only research-specific task data without interacting with user files. Tasks execute within sandboxed environments, such as virtual machines, to isolate computations and prevent potential spread or unauthorized access. Communications between clients, servers, and research institutions are encrypted, while applications are cryptographically signed to verify authenticity—unsigned versions are rejected. Regular audits, including code reviews by experts and automated vulnerability scans during software builds, are conducted to maintain compliance with standards like those of Compute . Mitigations for reliability issues include task replication, where results are validated by running computations on multiple (typically two to five) independent devices to achieve consensus through bitwise agreement or custom equivalence checks, minimizing errors from faulty hardware or malice. Fault-tolerant scheduling employs policies like weighted round-robin and runtime estimations based on floating-point operations per second (FLOPs) and host performance to distribute work efficiently despite churn and heterogeneity. Community forums provide a platform for volunteers to report and troubleshoot issues, fostering collaborative problem-solving. In 2025, WCG faced challenges during its full migration from the Graham to the Nibi cloud facilities, which required an extended from August 31 onward to decommission the legacy infrastructure without disrupting ongoing computations. This process was resolved successfully by September 18, 2025, with all endpoints operational and no reported , ensuring seamless continuation of volunteer contributions. Following the successful migration to the Nibi cloud in September 2025, the platform has remained operational, with device profile updates implemented in November 2025 to optimize task allocation.

Research Projects

Project Selection and Management

The selection of research projects for World Community Grid begins with proposals submitted by non-profit organizations or academic institutions focused on humanitarian challenges, such as , , or alleviation. These proposals must demonstrate a need for large-scale to advance that benefits humanity, particularly in underserved areas. The World Community Grid team, in collaboration with a scientific comprising prominent scientists, philanthropists, and experts, reviews submissions quarterly to ensure alignment with these goals. Proposals are first pre-qualified against six key criteria: clear goals and anticipated societal impact; compatibility with , requiring algorithms that can be subdivided into millions of independent tasks; adequate independent funding for the research beyond computing resources; no concurrent use of other grids or supercomputers; sufficient organizational capacity to execute and disseminate results; and completeness of the proposal itself. Qualified proposals undergo further evaluation by external subject matter experts assessing scientific importance, innovation, feasibility, and potential for broad dissemination. Final approval is at the discretion of World Community Grid, leading to a Project Hosting Agreement that outlines collaboration on planning, execution, and result sharing. Up to five projects may be selected annually through this process. Once selected, projects are managed through structured phases to address computational demands efficiently, with researchers estimating required CPU hours upfront and developing specialized applications for volunteer devices. World Community Grid handles infrastructure, scheduling, and , allowing research teams to concentrate on scientific analysis while providing periodic progress updates to ensure alignment with objectives. Projects often progress in sequential phases, such as initial screening followed by validation, to build on interim results. Funding for projects is hybrid: The Krembil Research Institute covers all grid infrastructure and operational costs, while volunteer computing power is donated at no charge; researchers must secure their own grants for personnel, , and validation efforts. All results enter the to maximize global impact. Active projects continue indefinitely until research goals are met, typically spanning 2 to 5 years based on computational scope and accumulation needs, after which they transition to completion status with final reporting. This flexible duration allows adaptation to emerging findings while maintaining rigorous oversight.

Active Projects

As of November 2025, World Community Grid supports four active projects, centered on advancing health diagnostics and climate prediction through distributed . These initiatives—Africa Rainfall Project, Mapping Cancer Markers, OpenPandemics - , and Mapping Arthritis Markers—leverage the grid's vast computational resources to process complex datasets that would be impractical on traditional supercomputers. By harnessing idle devices from volunteers worldwide, the projects enable rapid analysis of large-scale biological and environmental , fostering breakthroughs in early detection and modeling. A unifying theme across these projects is the integration of and (AI/ML) techniques for data analysis, combined with real-world inputs such as patient-derived samples and established weather models. For instance, health-focused efforts like Mapping Cancer Markers and Mapping Arthritis Markers employ AI/ML algorithms developed by the Jurisica Lab and Schroeder Arthritis Institute to identify molecular signatures from clinical datasets, including tissue and biomarker profiles. Similarly, OpenPandemics utilizes molecular simulations informed by Scripps Research's AI-driven approaches to screen compounds against viral targets, while the Africa Rainfall Project incorporates University's high-resolution simulations with ML-enhanced post-processing of and gauge data for rainfall estimation. This AI/ML emphasis allows for and predictive modeling at scales unattainable without distributed resources. Collectively, these projects aim to accelerate scientific discoveries that address global challenges, such as and , by democratizing access to . The volunteer model has seen a notable surge in task processing following 2025 infrastructure upgrades, including the full migration to the Nibi cloud platform, which enhanced scalability and reduced downtime. Cross-project elements include standardized validation protocols to ensure result accuracy across simulations and analyses, as well as volunteer engagement tools like badges awarded for contributions to multiple projects, encouraging sustained participation.

Africa Rainfall Project

The Africa Rainfall Project, launched on October 30, 2019, by World Community Grid in partnership with researchers from , seeks to enhance rainfall prediction accuracy for farmers in . By generating high-resolution simulations of localized rainstorms, the initiative addresses the critical need for reliable weather data in a region where 95% of relies on rainfall, helping to inform crop planning and mitigate drought risks amid . The project's methodology centers on the Weather Research and Forecasting (WRF) model configured at 1 km resolution to simulate rainfall patterns across , leveraging the power of global volunteers. This approach integrates diverse data sources, including satellite observations, ground-based measurements from networks like the Trans-African Hydro-Meteorological Observatory (TAHMO), and precipitation data from , to produce detailed estimates of convective storms that coarser global models often miss. In 2025, the project resumed full operations on November 4, 2024, after a nearly two-year pause due to technical constraints that began in December 2022. A July 2025 update reported that volunteers had generated over 10.5 million results, completing two-thirds of the targeted rainfall , with ongoing task production expected to wrap up the full within approximately 12 months. These demonstrate marked accuracy gains, capturing 80% of rainfall from convective storms—far surpassing the performance of lower-resolution models like ERA5 at 31 km—thus enabling more precise local forecasts. The expected outcomes include the creation of accessible forecasting tools that empower sub-Saharan farmers to optimize planting and harvesting schedules, ultimately bolstering agricultural resilience and in vulnerable communities.

Mapping Cancer Markers

The Mapping Cancer Markers project launched on November 8, 2013, in partnership with the at the in , , led by Dr. Igor Jurisica. The initiative focuses on analyzing genomic and proteomic data from thousands of patient samples, including healthy and cancerous tissues from , ovarian, , pancreatic, and cancers, to identify patterns of molecular markers associated with disease progression and treatment outcomes. The project's methods leverage the distributed volunteer computing power of World Community Grid to perform large-scale of potential molecular markers. By processing combinations of chemical signatures from tissue and samples, the approach enables that links specific markers to cancer types, early detection risks, and responses to therapies, accelerating what would otherwise require extensive supercomputing resources. This integration with the broader active projects on allows seamless contribution from volunteers' devices. As of 2025, the project has analyzed millions of data points across multiple cancer datasets, including phases on , ovarian, and cancers, yielding insights into high-scoring . A key update in May 2025 highlighted the PDE8B , which encodes phosphodiesterase 8B involved in hormone synthesis and shows altered expression in various cancers; in subtypes, higher PDE8B levels serve as a beneficial prognostic marker associated with improved patient survival. The overarching goals center on developing tools for , such as biomarkers for earlier diagnostics, risk stratification for high-risk individuals, and tailored treatment strategies to enhance cancer care efficacy.

OpenPandemics -

The OpenPandemics - project was launched on April 1, 2020, as an urgent response to the escalating global caused by the virus. Developed by scientists at in collaboration with IBM's World Community Grid, the initiative harnesses and to rapidly screen millions of chemical compounds for potential therapeutic candidates. This effort aims to accelerate by identifying molecules that could inhibit or mitigate severe symptoms, with all generated data made openly available to the global research community to foster further collaboration. At its core, the project utilizes techniques to evaluate drug candidates against critical proteins, such as the main protease (Mpro), , and . Volunteers contribute by running distributed molecular docking simulations on their devices using the Vina software, which predicts binding affinities between compounds and target proteins to prioritize promising leads for experimental validation. These AI-driven computations enable the exploration of vast chemical libraries—far beyond what traditional lab-based screening could achieve in the same timeframe—focusing on repurposing existing drugs and novel molecules to disrupt viral processes. By 2025, the project remains active, with ongoing refinements to its computational models in light of post-initial pandemic waves and the emergence of variants like sublineages. Updates include new work units targeting additional viral , such as polymerases, and integration of variant-specific structural to enhance accuracy for evolving strains. Cumulatively, volunteers have completed over 632 million tasks, generating petabytes of simulation that continue to inform antiviral . Key impacts include the identification of several potential antivirals, particularly compounds that target —a major driver of severe outcomes—alongside direct inhibitors of viral proteins. For instance, computational results have highlighted FDA-approved drugs and developmental candidates with strong binding potential, some of which are advancing to and testing for efficacy against infection and associated storms. These contributions underscore the project's role in expediting therapeutic options for and preparing for future threats.

Mapping Arthritis Markers

The Mapping Arthritis Markers project, launched in early 2025, is led by researchers at the Krembil Research Institute through the Schroeder Arthritis Institute in . It focuses on analyzing biosamples, specifically skin samples from lesioned and non-lesioned areas of patients with and (PsA), to identify molecular markers that predict disease development, progression, and response to treatment. The project employs high-throughput data processing powered by World Community Grid volunteers to examine genomic variants, protein expressions, and immune responses in these biosamples. Building on advanced algorithms similar to those used in the Mapping Cancer Markers project, it incorporates AI-driven classification to distinguish PsA subtypes and uncover combinations of markers associated with disease severity. This approach also investigates gene-environment interactions, such as how genetic factors interact with triggers like infections or to influence onset. As of November 2025, the project continues active task generation, with volunteers having contributed to initial beta tasks and early . Early results highlight potential insights into gene-environment interactions that could refine risk stratification for PsA patients. The ultimate goals are to enable earlier diagnostics through panels and support the development of targeted therapies for PsA and related autoimmune diseases, potentially benefiting the estimated 3% of the global population affected by , many of whom develop .

Completed Projects

Since its launch in 2004, the World Community Grid has completed 31 projects, beginning with the Human Proteome Folding project in 2004. These efforts represent an archive of foundational contributions, with all generated data transferred to principal investigators for ongoing analysis, validation, and integration into broader scientific workflows. The completed projects emphasize themes of health and disease prevention, comprising the majority—such as initiatives targeting cancer, , , Zika, , and —with notable representation in environmental sustainability (e.g., clean water access and materials) and (e.g., enhancing rice nutrition for global ). Many projects unfold in iterative phases, where initial exploratory stages identify promising leads, followed by validation and refinement in subsequent phases to build cumulative knowledge. Upon completion, computational results are formally delivered to teams for peer-reviewed and application, while the platform's volunteer resources are dynamically reallocated to active or emerging initiatives to maintain continuous productivity. Volunteers receive notifications regarding completions, ensuring awareness of impacts and opportunities to support new work. Collectively, these projects have harnessed over 2.6 million years of donated computing power, delivering a scale equivalent to petascale supercomputing that enables humanitarian otherwise inaccessible due to resource constraints. This legacy underscores the grid's role in accelerating basic science across disciplines.

Medical and Disease-Focused Projects

The World Community Grid has supported a series of completed projects dedicated to advancing against human s, leveraging to perform computationally intensive tasks such as and virtual drug screening. These initiatives have primarily targeted cancer, , muscular dystrophy, and , including dengue fever, , tuberculosis, and leishmaniasis, which disproportionately affect underserved populations. By harnessing , the projects enabled researchers to analyze vast datasets that would otherwise require years of dedicated supercomputing resources, focusing on through molecular docking simulations and genomic analyses to uncover mechanisms. Key early efforts included the Human Proteome Folding projects in Phases 1 and 2 (2007-2010), which predicted the three-dimensional structures of thousands of human proteins using the Rosetta software suite to facilitate drug design and biomarker identification for various diseases, including cancer and pathogens like Plasmodium for malaria. Similarly, Help Defeat Cancer (2007-2009) employed automated image processing of tissue microarrays to examine biomarkers across hundreds of cancer specimens, enhancing the objectivity and scale of pattern recognition for improved tumor classification and therapy selection. Help Cure Muscular Dystrophy in Phases 1 and 2 (2007-2010) investigated protein-protein interactions in neuromuscular disorders by modeling over 10,000 known structures, aiming to reveal therapeutic targets for conditions like facioscapulohumeral muscular dystrophy. Subsequent projects emphasized antiviral drug discovery for infectious diseases. Discovering Dengue Drugs in Phases 1 and 2 (2009-2012) screened potential inhibitors against proteins, alongside related flaviviruses like West Nile and , using docking simulations to identify lead compounds for affecting millions annually. The GO Fight Against project (2008-2011) targeted drug-resistant strains by virtually screening compounds against proteins, prioritizing affordable treatments for a causing over 400,000 deaths yearly. Influenza Antiviral Drug Search (2011-2012) focused on docking simulations to find broad-spectrum antivirals effective against evolving flu strains, addressing gaps in preparedness. HIV/AIDS research advanced through FightAIDS@Home in Phases 1 and 2 (2007-2018), which utilized AutoDock and Vina tools to evaluate millions of chemical compounds against HIV enzymes like protease and integrase, processing data equivalent to over 340,000 years of volunteer computing time and identifying experimentally validated allosteric binding sites for novel inhibitors. Later projects tackled emerging and persistent threats: Outsmart Ebola Together (2014-2016) screened compounds for Ebola virus proteins to combat its high fatality rate, while OpenZika (2016-2018) targeted the virus's neurological impacts through similar docking approaches. Help Stop TB (2017-2020) analyzed Mycobacterium tuberculosis structures for new antibiotics, focusing on drug-resistant variants. Smash Childhood Cancer (2017-2021) expanded neuroblastoma drug searches across multiple pediatric cancers, building on prior efforts since 2009. The Microbiome Immunity Project (2019-2022) examined trillions of bacterial genetic sequences to link microbiome variations with immune responses in diseases like inflammatory bowel disorder. Additional initiatives addressed other , such as Say No to Schistosoma (2012-2015), which docked compounds against schistosome proteins to develop treatments for the parasitic infection affecting over 200 million people, and Drug Search for Leishmaniasis (2012-2014), which screened for inhibitors of enzymes to tackle a vector-borne causing significant morbidity in tropical regions. These projects collectively emphasized computational efficiency in docking simulations, enabling the evaluation of vast chemical libraries to prioritize candidates for lab validation, and highlighted World Community Grid's role in addressing underfunded areas of global health research.

Environmental and Climate Projects

World Community Grid's environmental and climate projects have leveraged to tackle challenges in modeling and sustainable resource management, with a particular emphasis on applications for developing regions. These completed initiatives utilized large-scale simulations of atmospheric models to predict regional variations and simulations to explore materials for clean water and energy solutions. By distributing computational tasks to volunteers' devices, the projects enabled researchers to process vast datasets that would otherwise require supercomputing resources, contributing to global efforts in adaptation and resource optimization. The AfricanClimate@Home project focused on developing more accurate regional climate models for Africa to better forecast the impacts of on , , and . Researchers at the used to test combinations of parameterizations in regional climate models with 30km grid resolution, downscaling coarser global models to simulate local atmospheric processes like rainfall patterns influenced by Africa's . The project emphasized applications for vulnerable developing regions, providing foundational data to support strategies in sectors such as and health, aligning with broader initiatives for in . Computing for Clean Water investigated molecular-scale water flow through filters to improve purification technologies for the nearly one billion people lacking access to clean water. The team at the employed simulations to explore flow regimes previously inaccessible due to computational limits, revealing that interactions—vibrations in the nanotube structure—enhance water diffusion rates by up to five times under realistic conditions. These findings, validated in subsequent lab experiments, have guided the design of more efficient, low-cost filtration materials with potential for widespread deployment in resource-limited areas. The project concluded after volunteers contributed nearly 100 million calculations, as detailed in a 2015 Nature Nanotechnology paper. The Clean Energy Project, led by , aimed to accelerate the discovery of organic materials for efficient solar cells and to combat through . Using calculations on volunteer computers, the team screened over 2.3 million candidate molecules for photovoltaic properties, identifying more than 35,000 with potential to double the efficiency of organic solar cells compared to traditional silicon-based ones. This high-throughput approach, powered by World Community Grid, narrowed down promising candidates for synthesis and testing, with results shared in peer-reviewed publications and influencing subsequent on low-cost solar technologies. The project wrapped up its phases by 2017, highlighting the role of computational screening in innovation. Computing for Sustainable Water examined the impacts of human activities on the watershed to inform restoration efforts and sustainable management. Researchers from the modeled nutrient flows, pollution, and ecological responses across 64,000 square kilometers using agent-based simulations that incorporated data from 16.7 million residents' behaviors. The computations revealed key interactions between , , and , providing insights for policy decisions on and conservation to mitigate . Concluded in 2012 after extensive volunteer contributions, the project underscored the value of large-scale modeling for regional .

Agriculture and Sustainability Projects

The World Community Grid has supported completed projects aimed at enhancing through advancements in crop genetics and , particularly focusing on staple crops like to address and in developing regions. The flagship initiative in this area, Nutritious Rice for the World, launched in May 2008 and concluded its computational phase in 2010, with key findings released in 2017. This project utilized distributed to predict the three-dimensional structures of over 60,000 rice proteins across major strains, including indica and japonica varieties, generating approximately 10 billion protein models. Methods employed in the project involved advanced algorithms developed by the ’s Research Group, applied to genome sequences via and modeling on World Community Grid's volunteer resources. These computations enabled the identification of protein functions related to nutrient uptake, yield, and stress tolerance, facilitating targeted breeding efforts. In collaboration with the (IRRI), which contributed institutional computing power and expertise in rice breeding, the project supported the integration of these models into practical applications for developing nutrient-enhanced varieties. Upon completion, the Nutritious Rice project outcomes included a publicly available database of protein structures that aided programs by pinpointing genes associated with higher and content in grains, such as those influencing provitamin A and iron accumulation. This contributed to policy impacts in and , where is a dietary staple for over half the world's population, helping to reduce deficiencies and support alleviation through improved resilience and . Despite its relatively smaller scale compared to medical projects, the initiative demonstrated high potential for by accelerating gene discovery for climate-adaptive, nutrient-dense crops without exhaustive field trials.

Scientific Contributions

Key Discoveries and Publications

The World Community Grid (WCG) has enabled the publication of over 180 peer-reviewed papers in leading scientific journals, spanning fields from infectious disease treatment to . These outputs demonstrate high , with seminal works such as the 2011 Genome Research paper from the Human Proteome Folding project garnering hundreds of citations for its proteome-scale structural predictions. Overall, WCG-supported research has produced influential contributions, prioritizing validated computational screening results that guide experimental validation. A notable breakthrough came from the FightAIDS@Home project, where massive-scale binding free energy simulations identified 38 compounds exhibiting high binding affinity to wild-type integrase, offering potential as novel antiviral agents. This 2019 study in the Journal of Chemical Information and Modeling highlighted the efficacy of in prioritizing drug candidates against mutants. Similarly, the Clean Energy Project utilized WCG to screen over 2.4 million organic photovoltaic candidates, uncovering more than 35,000 materials with properties capable of doubling the efficiency of organic solar cells compared to existing benchmarks. Key findings were published in the Journal of Physical Chemistry Letters in 2011, establishing a foundational for materials design in . In infectious disease research, the OpenZika project yielded several hit compounds, including 8 demonstrating micromolar inhibitory activity against targets in , with low profiles suitable for further development as antivirals. Detailed in a 2023 ACS Infectious Diseases , these results stemmed from docking over 100 million compounds against Zika proteins, informing targeted analog synthesis. The Discovering Dengue Drugs project advanced therapeutic pipelines by identifying a that binds and disables a critical dengue , halting across flaviviruses like West ; this candidate, refined for potency, is progressing toward preclinical testing. Likewise, findings from Help Cure Muscular Dystrophy elucidated key protein-protein interactions underlying neuromuscular disorders, supporting advancements in strategies through publications in Proteins: , Function, and Bioinformatics (2018–2019). Recent WCG efforts continue to drive outputs, as seen in the Microbiome Immunity Project's prediction of nearly 200,000 unique protein structures, revealing over 150 novel folds that enhance understanding of immune-microbe interactions; these have informed ongoing 2023–2025 publications in microbiome-focused journals.

Broader Impact on Research

World Community Grid has significantly expanded computational capacity for scientific research in under-resourced areas, such as tropical diseases, by harnessing power equivalent to some of the world's fastest supercomputers. This distributed infrastructure allows researchers to perform simulations and analyses that would otherwise be infeasible due to limited funding or access to resources. For instance, Fight Against project utilized this power to screen millions of chemical compounds for potential treatments, compressing what would have taken over a century into roughly one year. The project's outputs have informed global policy efforts, particularly through contributions to the (SDGs). Research from initiatives like Nutritious Rice for the World has advanced crop resilience, aligning with SDG 2 (Zero Hunger) by enhancing in vulnerable regions. Similarly, projects such as Computing for Clean Water support SDG 6 (Clean Water and Sanitation) by modeling processes, while health-focused efforts like those on and bolster SDG 3 (Good Health and Well-Being). These alignments demonstrate how World Community Grid's data and findings integrate into international frameworks for addressing global challenges. In addition to direct research acceleration, World Community Grid has fostered educational and methodological advancements in . It has trained in leveraging volunteer-based grids for large-scale simulations, enabling labs to adopt these techniques for ongoing work that might otherwise lack sufficient resources. The platform has also inspired the creation of similar networks, promoting broader adoption of crowdsourced computation in humanitarian science. Over the long term, World Community Grid has accelerated the development of open-access datasets, facilitating further and across institutions. By avoiding the need for expensive dedicated supercomputing , it has generated substantial economic value through cost savings in computational resources, allowing funds to be redirected toward experimental validation and fieldwork.

Outreach and Community

Engagement Strategies

World Community Grid employs a range of digital strategies to attract new volunteers and foster ongoing participation in its efforts. Online campaigns encourage individuals to donate spare power by highlighting the tangible benefits to humanitarian , such as advancing treatments for diseases and sustainable technologies, often shared through dedicated toolkits that include shareable videos and widgets for personal websites. Social media plays a key role in awareness-building and community interaction, with the official account @WCGrid posting updates on project milestones, volunteer achievements, and calls to action for participation. Volunteers can integrate their accounts to automatically share badge earnings and contribution stats, amplifying personal impact and motivating peers to join. newsletters provide regular progress updates on outcomes and volunteer contributions, keeping the community informed and engaged with content like scientific highlights and calls for increased device runtime. To enhance motivation, the platform incorporates elements, including multi-level badges awarded based on cumulative runtime per project—ranging from 11 levels that recognize escalating contributions—and team-based leaderboards that track points and results across global challenges. These features create a sense of accomplishment and friendly competition, encouraging sustained involvement. Virtual events further drive engagement, such as periodic All Projects Challenges that rally teams to maximize results returned or runtime in themed competitions, like quarterly points-based contests that have historically boosted collective output. Retention is supported through personalized dashboards on the "My Contribution" page, where volunteers view detailed stats on their device's impact, such as the number of compounds screened or computations completed, reinforcing the real-world value of their efforts. Inclusivity is prioritized to broaden global reach, alongside community advisors fluent in various languages to assist diverse users. Efforts also target underrepresented regions by promoting participation through accessible platforms and emphasizing the universal benefits of the research.

Partnerships, Awards, and Recognition

Key academic partnerships have driven the project's scientific output, notably with Scripps Research Institute in La Jolla, California, which has collaborated on multiple initiatives including FightAIDS@Home (launched in 2007 to design anti-HIV drugs) and OpenPandemics (2020, focusing on COVID-19 treatments through virtual drug screening). These collaborations exemplify the grid's model of leveraging volunteer computing to support nonprofit research institutions, with Scripps utilizing the platform to process billions of chemical compounds for potential therapeutics. The University of Toronto, through its Jurisica Lab at UHN, continues to oversee project management and integration with broader computational resources. The project's contributions have earned international accolades for innovation in humanitarian computing. In recognition of its impact, World Community Grid received the Computerworld Data+ Editors' Choice Award for advancing data-driven social good, the Business in the Community Coffey International Award for corporate responsibility, and the Asian Forum on Asian CSR Award. These honors highlight its role in mobilizing global volunteer resources for public benefit, with UHN devoting more than C$539 million annually to as of 2024 that benefits from the grid's outputs. Further recognition came during its 20th anniversary in November 2024, celebrated through community updates emphasizing over 2.6 million years of donated computing power and over 186 peer-reviewed publications enabled by the platform. In 2025, the project underwent a full migration to the Nibi cloud infrastructure, supported by the Digital Research Alliance of Canada (formerly Compute Canada), ensuring scalable access to for ongoing research without disrupting volunteer contributions. This upgrade underscores sustained institutional support for the grid's collaborative framework, where partners like and UHN facilitate joint efforts without direct volunteer costs.

Comparisons and Statistics

Performance Metrics

World Community Grid has processed over 7.67 billion results, representing the total tasks completed by volunteers since its inception in 2004. This cumulative output underscores the platform's scale, with total computing contributions equivalent to more than 2.683 million years of CPU time. Efficiency metrics highlight the project's optimization for volunteer hardware. The average CPU time required per task is approximately 3 hours, derived from the overall run time divided by results returned, enabling effective utilization of idle processing cycles across diverse devices. Validation processes, including redundant computations where multiple devices process the same work unit and compare outcomes, maintain reliability by discarding inconsistent results. During the 2020 launch of the OpenPandemics - project, volunteer participation surged, accelerating task throughput as researchers rapidly screened millions of molecular compounds for potential treatments. This period exemplified peak performance, with heightened global engagement boosting daily processing capacity beyond baseline levels. In 2025, following the full migration to the Nibi cloud infrastructure completed in late August, the platform enhanced operational efficiency to support sustained growth in computational output. Performance is tracked via real-time dashboards on the official website, displaying metrics such as results returned, points generated, and run time through interactive graphs. Annual research updates from project teams provide detailed overviews of throughput trends and efficiency improvements, often including visualizations of year-over-year growth.

with Other Volunteer Grids

World Community Grid (WCG) operates within a competitive landscape of volunteer computing initiatives, where it distinguishes itself through its broad humanitarian focus compared to more specialized projects. Key competitors include , which concentrates on simulations to advance research, achieving unprecedented scale with a peak performance of 1.5 exaFLOPS during the in 2020, far surpassing other efforts in raw computational power at that time. , led by the Baker Laboratory, emphasizes and design for biomedical applications, generating 237 scientific publications over 16 years. ClimatePrediction.net, an Oxford University initiative, targets climate modeling and environmental forecasting, producing 129 publications. In contrast, WCG's umbrella structure supports 31 diverse sub-projects across health, poverty alleviation, and sustainability, allowing volunteers to contribute to multiple humanitarian efforts without switching platforms. This breadth is bolstered by its origins under IBM's corporate sponsorship, providing robust infrastructure and resources, unlike the primarily academic leadership of competitors such as and ClimatePrediction.net. Additionally, WCG uniquely emphasizes mobile participation, enabling Android devices and tablets to join alongside desktops, expanding beyond traditional PC-based . WCG's competitive advantages lie in its user-friendly design and engagement strategies, facilitating easier for newcomers through a single account that automatically allocates tasks across projects, reducing setup complexity compared to specialized platforms requiring separate installations. Volunteers can opt in or out of specific sub-projects, offering flexibility absent in single-focus initiatives like , which demands dedicated software. Outreach efforts, including partnerships with nonprofits and clear progress reporting, contribute to sustained participation, with WCG attracting over 818,448 members and 7.726 million devices that have collectively returned more than 7.67 billion results as of November 2025. In the broader volunteer computing ecosystem, WCG ranks among the top BOINC-based projects, accumulating 2.683 million years of total runtime as of November 2025, positioning it in the upper tier alongside Rosetta@home (221 teraFLOPS as of November 2025) but behind Folding@home's historical peaks. As a BOINC platform, WCG fosters collaborations, such as hosting sub-projects that leverage Rosetta software for protein folding tasks in initiatives like Human Proteome Folding, enabling shared computational efforts across the network without direct resource overlap. This interconnected approach enhances overall impact while maintaining WCG's focus on humanitarian applications.

References

  1. https://www.worldcommunitygrid.org/
  2. https://www.ibm.com/history/world-community-grid
  3. https://www.worldcommunitygrid.org/about_us/viewAbout.do
  4. https://www.worldcommunitygrid.org/stat/viewGlobal.do
  5. https://www.worldcommunitygrid.org/about_us/article.s?articleId=816
  6. https://www.worldcommunitygrid.org/help/topic.s?shortName=GPU
  7. https://blog.obyte.org/obyte-and-world-community-grid-join-the-fight-against-sars-cov-2-2917a43ab402
  8. https://www.worldcommunitygrid.org/research/opn1/overview.do
  9. https://www.technewsworld.com/story/ibm-builds-world-community-grid-for-scientific-research-38201.html
  10. https://indico.cern.ch/event/71570/contributions/1241456/attachments/1035145/1474836/slides.pdf
  11. https://pmc.ncbi.nlm.nih.gov/articles/PMC3205581/
  12. https://www.worldcommunitygrid.org/research/proteome/overview.s
  13. https://www.philanthropy.com/news/research-project-taps-free-computing-power/
  14. https://www.economist.com/technology-quarterly/2007/12/08/spreading-the-load
  15. https://www.worldcommunitygrid.org/help/topic.s?shortName=bnc
  16. https://www.worldcommunitygrid.org/about_us/article.s?articleId=318
  17. https://www.worldcommunitygrid.org/about_us/viewNewsArticle.do?articleId=203
  18. https://www.worldcommunitygrid.org/about_us/article.s?articleId=764
  19. https://www.worldcommunitygrid.org/about_us/news.s
  20. https://www.worldcommunitygrid.org/about_us/article.s?articleId=824
  21. https://www.worldcommunitygrid.org/about_us/article.s?articleId=826
  22. https://www.worldcommunitygrid.org/about/how.s
  23. https://boinc.berkeley.edu/trac/wiki/VolunteerComputing
  24. https://www.worldcommunitygrid.org/points.jsp
  25. https://www.worldcommunitygrid.org/help/viewTopic.do?shortName=wcgsoftware
  26. https://www.worldcommunitygrid.org/help/topic.s?shortName=install
  27. https://www.worldcommunitygrid.org/help/topic.s?shortName=minimumreq
  28. https://www.worldcommunitygrid.org/help/viewTopic.do?shortName=android
  29. https://www.worldcommunitygrid.org/help/viewSearch.do?searchString=android
  30. https://www.worldcommunitygrid.org/help/viewTopic.do?shortName=reg
  31. https://www.worldcommunitygrid.org/about/become.s
  32. https://www.worldcommunitygrid.org/help/topic.s?shortName=profile
  33. https://secure.worldcommunitygrid.org/ms/viewMyProjects.do
  34. https://arxiv.org/abs/1903.01699
  35. https://www.worldcommunitygrid.org/about/security.s
  36. https://www.worldcommunitygrid.org/help/viewTopic.do?shortName=aboutwcg
  37. https://boinc.berkeley.edu/forum_thread.php?id=14949&postid=117395
  38. https://www.worldcommunitygrid.org/bg/rfp.pdf
  39. https://hal-lara.archives-ouvertes.fr/hal-02102660/file/RR2007-49.pdf
  40. https://www.nbcnews.com/id/wbna6502699
  41. https://www.worldcommunitygrid.org/research/proposal.s
  42. https://www.worldcommunitygrid.org/about/about.s
  43. https://www.worldcommunitygrid.org/research/projects.s
  44. https://www.worldcommunitygrid.org/stat/viewProjects.do
  45. https://www.cs.toronto.edu/~juris/jlab/mcm.html
  46. https://www.cs.toronto.edu/~juris/jlab/publications.html
  47. https://www.uhnresearch.ca/researcher/divya-sharma
  48. https://www.scripps.edu/news-and-events/press-room/2023/20230721-balch-pandemics.html
  49. https://research.tudelft.nl/en/publications/the-potential-of-deep-learning-for-satellite-rainfall-detection-o
  50. https://www.worldcommunitygrid.org/research/arp1/overview.s
  51. https://www.worldcommunitygrid.org/research/mcm1/overview.s
  52. https://www.worldcommunitygrid.org/help/topic.s?shortName=web
  53. https://wcg.fandom.com/wiki/Project_badges
  54. https://www.worldcommunitygrid.org/about_us/viewNewsArticle.do?articleId=608
  55. https://africarain.readthedocs.io/en/latest/about.html
  56. https://worldcommunitygrid.org/images/prismic/WCG_Newsletter_Nov_2024.pdf
  57. https://www.worldcommunitygrid.org/about_us/viewNewsArticle.do?articleId=331
  58. https://www.worldcommunitygrid.org/research/mcm1/overview.do
  59. https://www.cs.toronto.edu/~juris/jlab/mcm/UPDATE-2019-DEC.pdf
  60. https://www.worldcommunitygrid.org/about_us/viewNewsArticle.do?articleId=823
  61. https://www.worldcommunitygrid.org/research/mcm1/faq.do
  62. https://www.scripps.edu/news-and-events/press-room/2020/20200401-OpenPandemics-covid19.html
  63. https://pmc.ncbi.nlm.nih.gov/articles/PMC7737764/
  64. https://forlilab.org/openpandemics-covid-19/
  65. https://www.worldcommunitygrid.org/research/opn1/news.do
  66. https://www.worldcommunitygrid.org/stat/viewProject.do?projectShortName=opn1
  67. https://forlilab.org/openpandemics-covid-19/opn-update-7-20/
  68. https://magazine.scripps.edu/translations/2021/fall/extensive-study-identifies-existing-drugs-as-potential-covid-19-therapies/
  69. https://www.worldcommunitygrid.org/research/mam1/overview.do
  70. https://www.uhnresearch.ca/news/getting-ahead-arthritis
  71. https://www.worldcommunitygrid.org/stat/viewProject.do?projectShortName=mam1
  72. https://www.psoriasis.org/psoriasis-statistics
  73. https://www.worldcommunitygrid.org/research/projects.s?proj=comp
  74. https://www.worldcommunitygrid.org/research/hpf1/overview.do
  75. https://www.worldcommunitygrid.org/images/prismic/WCG_Newsletter_Jan_2025.pdf
  76. https://autotweet.worldcommunitygrid.org/forums/wcg/viewpostinthread?post=672325
  77. https://www.worldcommunitygrid.org/research/proteome/overview.do
  78. https://www.worldcommunitygrid.org/research/hpf2/overview.do
  79. https://www.worldcommunitygrid.org/research/hdc/overview.do
  80. https://www.worldcommunitygrid.org/research/hcmd/overview.do
  81. https://www.worldcommunitygrid.org/research/hcmd2/overview.do
  82. https://www.worldcommunitygrid.org/research/dddt/overview.do
  83. https://www.worldcommunitygrid.org/research/dddt2/overview.do
  84. https://www.worldcommunitygrid.org/research/gfam/overview.do
  85. https://www.worldcommunitygrid.org/research/flu1/overview.do
  86. https://www.worldcommunitygrid.org/research/faah/overview.do
  87. https://www.worldcommunitygrid.org/research/fahb/overview.do
  88. https://www.worldcommunitygrid.org/about_us/viewNewsArticle.do?articleId=454
  89. https://www.worldcommunitygrid.org/research/oet1/overview.do
  90. https://www.worldcommunitygrid.org/research/zika/overview.do
  91. https://www.worldcommunitygrid.org/research/hst1/overview.do
  92. https://www.worldcommunitygrid.org/research/scc1/overview.do
  93. https://www.worldcommunitygrid.org/research/mip1/overview.do
  94. https://www.worldcommunitygrid.org/research/sn2s/overview.do
  95. https://www.worldcommunitygrid.org/research/dsfl/overview.do
  96. https://www.worldcommunitygrid.org/research/acah/overview.do
  97. https://www.worldcommunitygrid.org/projects_showcase/ach/viewAchAbout.do
  98. https://www.worldcommunitygrid.org/research/c4cw/overview.do
  99. https://www.worldcommunitygrid.org/about_us/article.s?articleId=355
  100. https://worldcommunitygrid.org/research/cep1/overview.do
  101. https://www.prnewswire.com/news-releases/using-ibms-crowdsourced-supercomputer-harvard-rates-solar-energy-potential-of-23-million-new-compounds-212746251.html
  102. https://www.worldcommunitygrid.org/research/cfsw/overview.do
  103. https://www.worldcommunitygrid.org/about_us/viewNewsArticle.do?articleId=208
  104. https://news.virginia.edu/content/ibm-uva-launch-computing-sustainable-water-project
  105. https://www.worldcommunitygrid.org/research/rice/overview.do
  106. https://www.worldcommunitygrid.org/about_us/article.s?articleId=126
  107. https://www.researchgate.net/publication/345752259_Rice_protein_models_from_the_Nutritious_Rice_for_the_World_Project
  108. http://books.irri.org/RT8_4_content.pdf
  109. https://equn.com/forum/thread-28443-3-1.html
  110. https://www.worldcommunitygrid.org/about_us/article.s?articleId=516
  111. https://www.irri.org/news-and-events/news/close-look-irri-nutrition
  112. https://www.cs.toronto.edu/~juris/jlab/wcg.html
  113. https://pubs.acs.org/doi/10.1021/jz200866s
  114. https://pmc.ncbi.nlm.nih.gov/articles/PMC9923514/
  115. https://www.worldcommunitygrid.org/about_us/article.s?articleId=397
  116. https://worldcommunitygrid.org/research/gfam/overview.s
  117. https://www.scout.org/node/1296
  118. https://clp.law.harvard.edu/wp-content/uploads/2022/10/Bending-the-Curve-of-Life-9-30-2020.pdf
  119. https://cerncourier.com/a/citizen-cyberscience-the-new-age-of-the-amateur/
  120. https://www.nature.com/articles/s41524-020-00401-8
  121. https://www.worldcommunitygrid.org/about/spread.s
  122. https://x.com/WCGrid
  123. https://www.worldcommunitygrid.org/newsletters
  124. https://www.worldcommunitygrid.org/help/viewSearch.do?searchString=badges
  125. https://www.worldcommunitygrid.org/stat/viewStatsByTeamAT.do?sort=points
  126. https://www.worldcommunitygrid.org/team/challenge/viewTeamChallengeHistory.do?teamId=C1CF7BLM9W1&listType=3&sortBy=endDate&filterType=0&filterOpen=1&filterDays=0&pageNum=239
  127. https://www.techpowerup.com/forums/threads/wcg-challenge-updates-for-2023.308050/
  128. https://www.allpurpose.io/work/world-community-grid
  129. https://www.worldcommunitygrid.org/viewContactUs.do
  130. https://www.scripps.edu/news-and-events/press-room/2014/20141203worldgrid.html
  131. https://www.uhncommercialization.ca/2024-full-articles/the-future-of-canadas-economy-will-be-research-based
  132. https://www.worldcommunitygrid.org/about/partners.do
  133. https://www.worldcommunitygrid.org/help/viewTopic.do?shortName=points
  134. https://arstechnica.com/science/2020/04/how-the-pandemic-revived-a-distributed-computing-project-and-made-history/
  135. https://boinc.berkeley.edu/TESI%20pub%20en.pdf
  136. https://boinc.bakerlab.org/rosetta/cpu_list.php
  137. https://boinc.bakerlab.org/forum_thread.php?id=2679
Add your contribution
Related Hubs
User Avatar
No comments yet.