Folding project #14935, CANCER research

Research section Research projects and references

Project #14935 overview

Project Summary AI Beta

This project looks at Class F Receptors, which control how cells develop. Overactive receptors can cause cancer like Basal Cell Carcinoma and Medulloblastoma. By using computer models, researchers want to figure out how these receptors work, helping us understand and treat these diseases better.

Automated summary; simplified and may not be fully accurate.

Project team

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

Work unit

Atoms: 105,385
Core: OPENMM_22
Status: Public

Source material

Official 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.

Reading reference

Related Terms Glossary AI Beta

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

Class F Receptors

Receptors that play a role in cell differentiation.

Scientific: BiotechnologyCell Biology / Signal Transduction

Class F receptors are a type of protein found on the surface of cells. They receive signals from other molecules and help to control how cells grow and develop. Overactivation of these receptors has been linked to certain types of cancer, such as basal cell carcinoma and medulloblastoma.

Basal Cell Carcinoma

A common type of skin cancer that originates in the basal cells.

Medical: HealthcareOncology / Skin Cancer

Basal cell carcinoma is the most common form of skin cancer. It develops from the basal cells, which are located in the deepest layer of the epidermis (outermost layer of skin). Basal cell carcinomas typically appear as pearly or waxy bumps and can grow slowly.

Medulloblastoma

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

Medical: HealthcareOncology / Pediatric Brain Cancer

Medulloblastoma is a fast-growing brain tumor that occurs most often in children. It originates in the cerebellum, a part of the brain responsible for balance and coordination. Medulloblastoma can spread to other parts of the body.

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 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	7,251,972	139,965	51.81	0 ^hrs 28 ^mins
2	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	6,969,150	134,068	51.98	0 ^hrs 28 ^mins
3	GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti]	Nvidia	GA102	6,664,416	133,331	49.98	0 ^hrs 29 ^mins
4	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	5,827,244	129,417	45.03	0 ^hrs 32 ^mins
5	GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti]	Nvidia	GA104	4,637,443	120,492	38.49	0 ^hrs 37 ^mins
6	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	4,258,136	116,851	36.44	0 ^hrs 40 ^mins
7	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	3,961,025	114,338	34.64	0 ^hrs 42 ^mins
8	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	3,811,691	109,134	34.93	0 ^hrs 41 ^mins
9	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	3,757,657	113,078	33.23	0 ^hrs 43 ^mins
10	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	3,331,796	107,975	30.86	0 ^hrs 47 ^mins
11	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A]	Nvidia	TU106	2,480,383	97,607	25.41	0 ^hrs 57 ^mins
12	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] M 7465	Nvidia	TU106	2,420,675	97,296	24.88	0 ^hrs 58 ^mins
13	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	2,363,877	89,453	26.43	0 ^hrs 54 ^mins
14	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,269,840	95,171	23.85	1 ^hrs 0 ^mins
15	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	2,134,381	93,346	22.87	1 ^hrs 3 ^mins
16	GeForce RTX 2070 SUPER Mobile / Max-Q TU104M [GeForce RTX 2070 SUPER Mobile / Max-Q]	Nvidia	TU104M	2,121,486	84,404	25.13	0 ^hrs 57 ^mins
17	GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate]	Nvidia	GA106	2,022,654	91,024	22.22	1 ^hrs 5 ^mins
18	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	1,921,047	90,401	21.25	1 ^hrs 8 ^mins
19	GeForce RTX 3060 GA106 [GeForce RTX 3060]	Nvidia	GA106	1,848,409	88,869	20.80	1 ^hrs 9 ^mins

20	GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]	Nvidia	GA104M	1,637,992	85,308	19.20	1 ^hrs 15 ^mins
21	GeForce RTX 2070 TU106 [GeForce RTX 2070]	Nvidia	TU106	1,441,844	82,318	17.52	1 ^hrs 22 ^mins
22	GeForce RTX 2060 Mobile TU106M [GeForce RTX 2060 Mobile]	Nvidia	TU106M	1,409,852	81,035	17.40	1 ^hrs 23 ^mins
23	GeForce RTX 2070 TU106 [GeForce RTX 2070] M 6497	Nvidia	TU106	1,406,563	81,357	17.29	1 ^hrs 23 ^mins
24	GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186	Nvidia	GP104	1,306,136	78,073	16.73	1 ^hrs 26 ^mins
25	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	1,289,979	78,453	16.44	1 ^hrs 28 ^mins
26	GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632	Nvidia	GM200	1,220,980	77,447	15.77	1 ^hrs 31 ^mins
27	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	1,013,432	73,139	13.86	1 ^hrs 44 ^mins
28	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	913,106	65,915	13.85	1 ^hrs 44 ^mins
29	Tesla M40 GM200GL [Tesla M40] 6844	Nvidia	GM200GL	795,830	67,240	11.84	2 ^hrs 2 ^mins
30	GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372	Nvidia	GP106	684,446	64,382	10.63	2 ^hrs 15 ^mins
31	GeForce GTX 980 GM204 [GeForce GTX 980] 4612	Nvidia	GM204	551,678	58,411	9.44	2 ^hrs 32 ^mins
32	GeForce GTX 970 GM204 [GeForce GTX 970] 3494	Nvidia	GM204	489,396	57,073	8.57	2 ^hrs 48 ^mins
33	GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935	Nvidia	GP106	465,273	56,091	8.29	2 ^hrs 54 ^mins
34	GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138	Nvidia	GP107	331,061	50,318	6.58	3 ^hrs 39 ^mins
35	GeForce GTX 1650 TU117 [GeForce GTX 1650]	Nvidia	TU117	313,148	48,128	6.51	3 ^hrs 41 ^mins
36	GeForce GTX 960 GM206 [GeForce GTX 960] 2308	Nvidia	GM206	309,721	49,115	6.31	3 ^hrs 48 ^mins
37	Quadro P1000 GP107GL [Quadro P1000]	Nvidia	GP107GL	191,775	42,059	4.56	5 ^hrs 16 ^mins
38	GeForce GTX 770 GK104 [GeForce GTX 770] 3213	Nvidia	GK104	112,066	34,869	3.21	7 ^hrs 28 ^mins
39	GeForce GTX 760 GK104 [GeForce GTX 760] 2258	Nvidia	GK104	96,187	33,175	2.90	8 ^hrs 17 ^mins

40	GeForce GTX 660 GK106 [GeForce GTX 660]	Nvidia	GK106	67,493	29,736	2.27	10 ^hrs 34 ^mins
41	Quadro K1200 GM107GL [Quadro K1200]	Nvidia	GM107GL	50,766	26,888	1.89	12 ^hrs 43 ^mins
42	GeForce GT 730 GK208B [GeForce GT 730] 692.7	Nvidia	GK208B	30,103	22,720	1.32	18 ^hrs 7 ^mins

Research: CANCER Folding Project #14935

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 14935

GPU PPD Averages

Research: CANCER Folding Project #14935

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages