RESEARCH: CANCER
FOLDING PROJECT #14933 PROFILE

PROJECT TEAM

Manager(s): Prateek Bansal
Institution: University of Illinois Urbana-Champaign

WORK UNIT INFO

Atoms: 105,522
Core: OPENMM_22
Status: Public

Related Projects

TLDR; PROJECT SUMMARY AI BETA

This project looks at Class F Receptors, proteins that help control how cells grow and change. Too much activity in these proteins can cause cancers like Basal Cell Carcinoma and Medulloblastoma. By using computer simulations, researchers hope to understand how these proteins work so they can better study and treat these diseases.

Note: This TLDR is a simplication and may not be 100% accurate.

OFFICAL PROJECT DESCRIPTION

Class F Receptors Class F Receptors are involved in the control of cell differentiation.

Over-activation of these proteins have 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

Note: Glossary items are a high level summary and may not be 100% accurate.

Class F Receptors

Membrane proteins that bind to specific ligands and initiate intracellular signaling cascades.

Scientific: Biotechnology
Cellular Biology / Receptor Signaling

Class F receptors are a type of protein found on the surface of cells. They act as receptors, binding to specific molecules called ligands. This binding triggers a series of events inside the cell, known as signaling cascades, which ultimately regulate various cellular functions. These receptors play crucial roles in processes like cell growth, differentiation, and survival. Disruptions in their function can contribute to diseases such as cancer.


Basal Cell Carcinoma

A common type of skin cancer that arises from the basal cells in the epidermis.

Medical: Healthcare
Oncology / Skin Cancer

Basal cell carcinoma is the most prevalent form of skin cancer. It develops from the basal cells, which are located in the deepest layer of the epidermis (the outermost layer of skin). These tumors typically appear as pearly or waxy bumps and often have a visible blood vessel network. Basal cell carcinomas grow slowly and rarely spread to other parts of the body.


Medulloblastoma

A type of malignant brain tumor that originates in the cerebellum.

Medical: Healthcare
Oncology / Brain Tumors

Medulloblastoma is a highly aggressive form of childhood brain cancer. It arises from cells in the cerebellum, the part of the brain responsible for coordinating movement and balance. Medulloblastomas tend to grow rapidly and can spread to other parts of the nervous system.

PROJECT FOLDING PPD AVERAGES BY GPU

Data as of Tuesday, 14 April 2026 06:32:42
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 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 7,008,299 135,217 51.83 0 hrs 28 mins
2 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 6,691,256 135,120 49.52 0 hrs 29 mins
3 GeForce RTX 3080 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 5,889,361 128,621 45.79 0 hrs 31 mins
4 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 5,585,713 128,338 43.52 0 hrs 33 mins
5 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,676,418 120,278 38.88 0 hrs 37 mins
6 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 4,637,973 120,455 38.50 0 hrs 37 mins
7 RTX A5000
GA102GL [RTX A5000]
Nvidia GA102GL 4,423,720 118,999 37.17 0 hrs 39 mins
8 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,407,662 116,791 37.74 0 hrs 38 mins
9 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 4,044,320 115,116 35.13 0 hrs 41 mins
10 GeForce RTX 2080 Rev. A
TU104 [GeForce RTX 2080 Rev. A] 10068
Nvidia TU104 3,889,330 113,700 34.21 0 hrs 42 mins
11 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 3,179,202 106,269 29.92 0 hrs 48 mins
12 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 3,015,278 102,214 29.50 0 hrs 49 mins
13 GeForce RTX 2070 Rev. A
TU106 [GeForce RTX 2070 Rev. A]
Nvidia TU106 2,640,591 100,291 26.33 0 hrs 55 mins
14 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,249,969 94,967 23.69 1 hrs 1 mins
15 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 2,239,312 94,561 23.68 1 hrs 1 mins
16 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 2,127,963 93,591 22.74 1 hrs 3 mins
17 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 2,042,500 91,484 22.33 1 hrs 4 mins
18 GeForce RTX 2070
TU106 [GeForce RTX 2070] M 6497
Nvidia TU106 2,020,003 91,181 22.15 1 hrs 5 mins
19 GeForce RTX 2060
TU104 [GeForce RTX 2060]
Nvidia TU104 1,949,249 90,719 21.49 1 hrs 7 mins
20 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 1,809,944 87,899 20.59 1 hrs 10 mins
21 GeForce RTX 2070
TU106 [GeForce RTX 2070]
Nvidia TU106 1,746,503 87,795 19.89 1 hrs 12 mins
22 GeForce RTX 2060 Mobile
TU106M [GeForce RTX 2060 Mobile]
Nvidia TU106M 1,353,435 80,352 16.84 1 hrs 25 mins
23 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,290,917 78,597 16.42 1 hrs 28 mins
24 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 1,155,007 75,985 15.20 1 hrs 35 mins
25 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 1,090,026 72,652 15.00 1 hrs 36 mins
26 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,050,794 73,933 14.21 1 hrs 41 mins
27 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 905,083 69,782 12.97 1 hrs 51 mins
28 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 857,080 68,447 12.52 1 hrs 55 mins
29 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 801,305 67,149 11.93 2 hrs 1 mins
30 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 681,387 63,825 10.68 2 hrs 15 mins
31 GeForce RTX 2060 Mobile / Max-Q
TU106M [GeForce RTX 2060 Mobile / Max-Q]
Nvidia TU106M 657,519 40,941 16.06 1 hrs 30 mins
32 P104-100
GP104 [P104-100]
Nvidia GP104 642,927 61,202 10.50 2 hrs 17 mins
33 GeForce GTX 1650 Mobile / Max-Q
TU117M [GeForce GTX 1650 Mobile / Max-Q]
Nvidia TU117M 590,804 61,369 9.63 2 hrs 30 mins
34 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 588,988 61,078 9.64 2 hrs 29 mins
35 Tesla P40
GP102GL [Tesla P40] 11760
Nvidia GP102GL 559,104 60,181 9.29 2 hrs 35 mins
36 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 557,340 59,520 9.36 2 hrs 34 mins
37 GeForce GTX 1650
TU117 [GeForce GTX 1650]
Nvidia TU117 540,077 59,293 9.11 2 hrs 38 mins
38 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 287,726 47,813 6.02 3 hrs 59 mins
39 GeForce GTX 950
GM206 [GeForce GTX 950] 1572
Nvidia GM206 213,734 42,672 5.01 4 hrs 47 mins
40 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 197,572 42,672 4.63 5 hrs 11 mins
41 P106-090
GP106 [P106-090]
Nvidia GP106 164,668 39,037 4.22 5 hrs 41 mins
42 GeForce GTX 770
GK104 [GeForce GTX 770] 3213
Nvidia GK104 131,405 36,751 3.58 6 hrs 43 mins
43 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 128,996 36,612 3.52 6 hrs 49 mins
44 GeForce GTX 760
GK104 [GeForce GTX 760] 2258
Nvidia GK104 91,937 32,667 2.81 8 hrs 32 mins
45 GeForce GT 730
GK208B [GeForce GT 730] 692.7
Nvidia GK208B 30,128 22,721 1.33 18 hrs 6 mins
46 GeForce GT 720
GK208 [GeForce GT 720]
Nvidia GK208 13,291 16,200 0.82 29 hrs 15 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

Data as of Tuesday, 14 April 2026 06:32:42
Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make