RESEARCH: CANCER
FOLDING PROJECT #14944 PROFILE
PROJECT TEAM
Manager(s): Prateek BansalInstitution: University of Illinois Urbana-Champaign
WORK UNIT INFO
Atoms: 105,200Core: 0x22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
This project studies how Class F Receptors and Patched proteins control cell growth. These proteins are linked to cancer, so figuring out how they work could help us understand and treat diseases like Basal Cell Carcinoma and Medulloblastoma.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Class F Receptors and Patched Membrane Protein Class F Receptors and Patched are human proteins that are involved in the control of cell differentiation.
Over-activation/inactivation of these proteins has links to Basal Cell Carcinoma and Medulloblastoma.
Through simulations we aim to understand the activation mechanisms of these proteins, giving us a way to probe into the pathogenesis of the disease.
RELATED TERMS GLOSSARY AI BETA
Class F Receptors
Receptors that bind to signaling molecules and trigger cellular responses.
Class F receptors are a type of protein found on the surface of cells. They act like antennas, receiving signals from other molecules in the body. These signals can tell cells to grow, divide, or change shape. When these receptors don't work properly, it can lead to problems like cancer.
Patched Membrane Protein
A transmembrane protein that regulates the signaling pathway of Hedgehog.
Patched is a protein found on the surface of cells. It plays an important role in controlling cell growth and development. The Hedgehog pathway is a signaling system that tells cells when to grow, divide, and specialize. Patched acts as a brake on this pathway, preventing cells from growing too quickly. When Patched doesn't work properly, it can lead to uncontrolled cell growth and cancer.
Basal Cell Carcinoma
The most common type of skin cancer.
Basal cell carcinoma is a slow-growing type of skin cancer that starts in the basal cells, which are located in the deepest layer of the epidermis (the outer layer of skin). It usually appears as a pearly or waxy bump on the skin and can grow slowly over time. While it's rarely life-threatening, it can spread to nearby tissues if left untreated.
Medulloblastoma
A type of aggressive brain tumor that develops in the cerebellum.
Medulloblastoma is a fast-growing brain tumor that originates in the cerebellum, which is responsible for coordinating movement and balance. It's most common in children and can spread quickly to other parts of the brain and spinal cord. Treatment typically involves surgery, radiation therapy, and chemotherapy.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Tuesday, 14 April 2026 06:32:35|
Rank Project |
Model Name Folding@Home Identifier |
Make Brand |
GPU Model |
PPD Average |
Points WU Average |
WUs Day Average |
WU Time Average |
|---|---|---|---|---|---|---|---|
| 1 | GeForce RTX 4090 AD102 [GeForce RTX 4090] |
Nvidia | AD102 | 12,582,877 | 171,084 | 73.55 | 0 hrs 20 mins |
| 2 | GeForce RTX 4080 AD103 [GeForce RTX 4080] |
Nvidia | AD103 | 12,101,725 | 169,381 | 71.45 | 0 hrs 20 mins |
| 3 | GeForce RTX 4070 Ti AD104 [GeForce RTX 4070 Ti] |
Nvidia | AD104 | 10,301,357 | 163,486 | 63.01 | 0 hrs 23 mins |
| 4 | GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti] |
Nvidia | GA102 | 8,918,061 | 155,498 | 57.35 | 0 hrs 25 mins |
| 5 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 8,255,253 | 149,942 | 55.06 | 0 hrs 26 mins |
| 6 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 7,207,150 | 145,126 | 49.66 | 0 hrs 29 mins |
| 7 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 7,111,405 | 144,240 | 49.30 | 0 hrs 29 mins |
| 8 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 6,900,802 | 141,046 | 48.93 | 0 hrs 29 mins |
| 9 | GeForce RTX 3080 12GB GA102 [GeForce RTX 3080 12GB] |
Nvidia | GA102 | 6,519,488 | 137,001 | 47.59 | 0 hrs 30 mins |
| 10 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,412,238 | 131,318 | 41.21 | 0 hrs 35 mins |
| 11 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 4,657,691 | 124,853 | 37.31 | 0 hrs 39 mins |
| 12 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 4,486,598 | 123,154 | 36.43 | 0 hrs 40 mins |
| 13 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 3,998,741 | 117,915 | 33.91 | 0 hrs 42 mins |
| 14 | GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER] |
Nvidia | TU104 | 3,790,607 | 117,173 | 32.35 | 0 hrs 45 mins |
| 15 | Radeon RX 7900XT/XTX Navi 31 [Radeon RX 7900XT/XTX] |
AMD | Navi 31 | 3,566,177 | 114,128 | 31.25 | 0 hrs 46 mins |
| 16 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,485,994 | 113,937 | 30.60 | 0 hrs 47 mins |
| 17 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,379,956 | 110,535 | 30.58 | 0 hrs 47 mins |
| 18 | GeForce RTX 3070 Mobile / Max-Q GA104M [GeForce RTX 3070 Mobile / Max-Q] |
Nvidia | GA104M | 2,754,610 | 105,864 | 26.02 | 0 hrs 55 mins |
| 19 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 2,688,482 | 104,058 | 25.84 | 0 hrs 56 mins |
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| 20 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,683,493 | 104,089 | 25.78 | 0 hrs 56 mins |
| 21 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,484,206 | 102,213 | 24.30 | 0 hrs 59 mins |
| 22 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,324,355 | 99,686 | 23.32 | 1 hrs 2 mins |
| 23 | Radeon RX 6800/6800XT/6900XT Navi 21 [Radeon RX 6800/6800XT/6900XT] |
AMD | Navi 21 | 2,226,234 | 97,847 | 22.75 | 1 hrs 3 mins |
| 24 | GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q] |
Nvidia | GA106M | 1,657,028 | 87,895 | 18.85 | 1 hrs 16 mins |
| 25 | Geforce RTX 3050 GA106 [Geforce RTX 3050] |
Nvidia | GA106 | 1,471,414 | 84,904 | 17.33 | 1 hrs 23 mins |
| 26 | Radeon VII Vega 20 [Radeon VII] |
AMD | Vega 20 | 1,471,407 | 85,371 | 17.24 | 1 hrs 24 mins |
| 27 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,401,905 | 83,252 | 16.84 | 1 hrs 26 mins |
| 28 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,401,490 | 83,940 | 16.70 | 1 hrs 26 mins |
| 29 | Radeon RX 6700/6700XT/6800M Navi 22 XT-XL [Radeon RX 6700/6700XT/6800M] |
AMD | Navi 22 XT-XL | 1,299,643 | 81,990 | 15.85 | 1 hrs 31 mins |
| 30 | RTX A2000 GA106 [RTX A2000] |
Nvidia | GA106 | 1,296,422 | 81,513 | 15.90 | 1 hrs 31 mins |
| 31 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,290,072 | 81,306 | 15.87 | 1 hrs 31 mins |
| 32 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,249,109 | 78,884 | 15.83 | 1 hrs 31 mins |
| 33 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,070,919 | 77,240 | 13.86 | 1 hrs 44 mins |
| 34 | Radeon RX Vega 56/64 Vega 10 XL/XT [Radeon RX Vega 56/64] |
AMD | Vega 10 XL/XT | 687,004 | 54,976 | 12.50 | 1 hrs 55 mins |
| 35 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 677,791 | 65,851 | 10.29 | 2 hrs 20 mins |
| 36 | GeForce GTX 1650 TU117 [GeForce GTX 1650] 3091 |
Nvidia | TU117 | 639,767 | 65,079 | 9.83 | 2 hrs 26 mins |
| 37 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 543,754 | 61,441 | 8.85 | 2 hrs 43 mins |
| 38 | GeForce GTX 1660 TU116 [GeForce GTX 1660] |
Nvidia | TU116 | 541,298 | 46,831 | 11.56 | 2 hrs 5 mins |
| 39 | GeForce GTX 1060 Mobile GP106M [GeForce GTX 1060 Mobile] |
Nvidia | GP106M | 450,488 | 57,452 | 7.84 | 3 hrs 4 mins |
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| 40 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 324,110 | 51,492 | 6.29 | 3 hrs 49 mins |
| 41 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 230,116 | 45,986 | 5.00 | 4 hrs 48 mins |
| 42 | RX Vega M GL Polaris 22 XL [RX Vega M GL] |
AMD | Polaris 22 XL | 142,704 | 39,309 | 3.63 | 6 hrs 37 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Tuesday, 14 April 2026 06:32:35|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|