Folding project #14938, CANCER research

Research section Research projects and references

Project #14938 overview

Project Summary AI Beta

This project looks at Class F Receptors and Patched proteins. They help control how cells grow and change. When these proteins don't work right, it can lead to cancers like Basal Cell Carcinoma and Medulloblastoma. By using computer simulations, we hope to understand how these proteins work so we can better treat these diseases.

Automated summary; simplified and may not be fully accurate.

Project team

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

Work unit

Atoms: 133,139
Core: 0x22
Status: Public

Source material

Official 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.

Reading reference

Related Terms Glossary AI Beta

Automated high-level definitions; simplified and may not be fully accurate.

Class F Receptors

Proteins that bind to signaling molecules.

Technical: MedicineBiotechnology / Cellular Biology

Class F receptors are a type of protein found on the surface of cells. They act as sensors, binding to specific molecules that trigger changes inside the cell. This process is crucial for many cellular functions, including growth, differentiation, and survival.

Patched Membrane Protein

A protein that regulates cell signaling.

Technical: MedicineBiotechnology / Cellular Biology

Patched is a membrane protein that acts as a negative regulator of the Hedgehog signaling pathway. This pathway plays a critical role in development and tissue homeostasis. Mutations in Patched can lead to overactivation of the pathway, contributing to cancer development.

Basal Cell Carcinoma

A type of skin cancer.

Clinical: HealthcareMedicine / Oncology

Basal cell carcinoma is the most common type of skin cancer. It arises from the basal cells, which are located in the deepest layer of the epidermis. This cancer typically appears as a pearly or waxy bump and can grow slowly.

Medulloblastoma

A type of brain cancer.

Clinical: HealthcareMedicine / Neurology

Medulloblastoma is a malignant tumor that originates in the cerebellum, a part of the brain responsible for coordination and balance. This cancer is most common in children.

GPU PPD Averages

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	14,259,515	231,326	61.64	0 ^hrs 23 ^mins
2	GeForce RTX 3090 Ti GA102 [GeForce RTX 3090 Ti]	Nvidia	GA102	9,721,952	205,441	47.32	0 ^hrs 30 ^mins
3	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	7,754,616	187,822	41.29	0 ^hrs 35 ^mins
4	GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti]	Nvidia	GA102	7,580,716	187,748	40.38	0 ^hrs 36 ^mins
5	GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	7,083,585	185,184	38.25	0 ^hrs 38 ^mins
6	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	5,932,205	173,879	34.12	0 ^hrs 42 ^mins
7	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	4,995,365	165,267	30.23	0 ^hrs 48 ^mins
8	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	4,950,288	159,853	30.97	0 ^hrs 46 ^mins
9	GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti]	Nvidia	GA104	4,793,734	161,742	29.64	0 ^hrs 49 ^mins
10	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	4,706,321	162,535	28.96	0 ^hrs 50 ^mins
11	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	3,228,973	142,026	22.74	1 ^hrs 3 ^mins
12	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	3,227,908	143,220	22.54	1 ^hrs 4 ^mins
13	TITAN X GP102 [TITAN X] 6144	Nvidia	GP102	3,177,323	141,791	22.41	1 ^hrs 4 ^mins
14	RTX A4000 GA104GL [RTX A4000]	Nvidia	GA104GL	3,087,449	140,652	21.95	1 ^hrs 6 ^mins
15	GeForce RTX 2080 Super TU104 [GeForce RTX 2080 SUPER]	Nvidia	TU104	2,837,560	136,651	20.77	1 ^hrs 9 ^mins
16	Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT]	AMD	Navi 21	2,714,343	132,317	20.51	1 ^hrs 10 ^mins
17	A40 GA102GL [A40]	Nvidia	GA102GL	2,552,530	132,980	19.19	1 ^hrs 15 ^mins
18	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	2,426,159	130,057	18.65	1 ^hrs 17 ^mins
19	GeForce RTX 2070 TU106 [GeForce RTX 2070]	Nvidia	TU106	2,422,821	130,227	18.60	1 ^hrs 17 ^mins

20	GeForce RTX 3060 GA106 [GeForce RTX 3060]	Nvidia	GA106	2,250,144	126,160	17.84	1 ^hrs 21 ^mins
21	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,136,407	123,663	17.28	1 ^hrs 23 ^mins
22	Quadro RTX 4000 TU104GL [Quadro RTX 4000]	Nvidia	TU104GL	1,942,687	120,230	16.16	1 ^hrs 29 ^mins
23	GeForce RTX 3060 Mobile / Max-Q GA106M [GeForce RTX 3060 Mobile / Max-Q]	Nvidia	GA106M	1,892,504	119,632	15.82	1 ^hrs 31 ^mins
24	GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate]	Nvidia	GA106	1,815,021	113,438	16.00	1 ^hrs 30 ^mins
25	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	1,544,596	111,511	13.85	1 ^hrs 44 ^mins
26	GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti]	Nvidia	TU116	1,531,046	110,869	13.81	1 ^hrs 44 ^mins
27	GeForce RTX 3050 Ti Mobile GA107M [GeForce RTX 3050 Ti Mobile]	Nvidia	GA107M	1,363,214	107,735	12.65	1 ^hrs 54 ^mins
28	Geforce RTX 3050 GA106 [Geforce RTX 3050]	Nvidia	GA106	1,349,728	106,426	12.68	1 ^hrs 54 ^mins
29	Tesla T4 TU104GL [Tesla T4]	Nvidia	TU104GL	1,349,703	107,795	12.52	1 ^hrs 55 ^mins
30	GeForce GTX 1660 Mobile TU116M [GeForce GTX 1660 Mobile]	Nvidia	TU116M	1,318,187	105,865	12.45	1 ^hrs 56 ^mins
31	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	1,267,036	103,470	12.25	1 ^hrs 58 ^mins
32	GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q]	Nvidia	TU106M	1,261,951	105,040	12.01	1 ^hrs 60 ^mins
33	Radeon RX 6700/6700 XT/6750 XT / 6800M Navi 22 [Radeon RX 6700/6700 XT/6750 XT / 6800M]	AMD	Navi 22	1,207,671	99,629	12.12	1 ^hrs 59 ^mins
34	Tesla M40 GM200GL [Tesla M40] 6844	Nvidia	GM200GL	1,091,900	99,695	10.95	2 ^hrs 11 ^mins
35	GeForce GTX 1660 TU116 [GeForce GTX 1660]	Nvidia	TU116	982,306	97,025	10.12	2 ^hrs 22 ^mins
36	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	978,452	96,101	10.18	2 ^hrs 21 ^mins
37	Radeon RX 6650 XT Navi 23 [Radeon RX 6650 XT]	AMD	Navi 23	962,874	95,494	10.08	2 ^hrs 23 ^mins
38	GeForce GTX 1650 SUPER TU116 [GeForce GTX 1650 SUPER]	Nvidia	TU116	830,252	92,187	9.01	2 ^hrs 40 ^mins
39	Radeon RX 6600/6600 XT/6600M Navi 23 [Radeon RX 6600/6600 XT/6600M]	AMD	Navi 23	825,523	89,715	9.20	2 ^hrs 36 ^mins

40	Radeon PRO W6600 Navi 23 WKS-XL [Radeon PRO W6600]	AMD	Navi 23 WKS-XL	749,223	85,478	8.77	2 ^hrs 44 ^mins
41	GeForce GTX 980 GM204 [GeForce GTX 980] 4612	Nvidia	GM204	669,991	84,590	7.92	3 ^hrs 2 ^mins
42	GeForce GTX 1650 Mobile / Max-Q TU117M [GeForce GTX 1650 Mobile / Max-Q]	Nvidia	TU117M	633,498	83,468	7.59	3 ^hrs 10 ^mins
43	GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138	Nvidia	GP107	357,185	70,872	5.04	4 ^hrs 46 ^mins
44	Radeon Pro W5700 Navi 10 [Radeon Pro W5700]	AMD	Navi 10	346,793	67,467	5.14	4 ^hrs 40 ^mins
45	Radeon RX 5600 OEM/5600 XT/5700/5700 XT Navi 10 [Radeon RX 5600 OEM/5600 XT/5700/5700 XT]	AMD	Navi 10	262,556	62,164	4.22	5 ^hrs 41 ^mins
46	GeForce MX450 TU117M [GeForce MX450]	Nvidia	TU117M	143,915	51,295	2.81	8 ^hrs 33 ^mins
47	Radeon RX 5500/5500M / Pro 5500M Navi 14 [Radeon RX 5500/5500M / Pro 5500M]	AMD	Navi 14	120,310	46,620	2.58	9 ^hrs 18 ^mins
48	Quadro K2200 GM107GL [Quadro K2200]	Nvidia	GM107GL	81,309	41,990	1.94	12 ^hrs 24 ^mins

Research: CANCER Folding Project #14938

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 14938

GPU PPD Averages

Research: CANCER Folding Project #14938

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages