Folding project #14932, CANCER research

Research section Research projects and references

Project #14932 overview

Project Summary AI Beta

This project looks at Class F Receptors, which help control how cells develop. When these receptors are overactive, it can lead to cancers like Basal Cell Carcinoma and Medulloblastoma. By using computer simulations, researchers hope to learn how these receptors work so they can better understand and 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: 105,129
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

A family of G protein-coupled receptors involved in cell differentiation.

Scientific: BiotechnologyCellular Biology / Signaling Pathways

Class F Receptors are a type of protein found on the surface of cells. They play a crucial role in regulating how cells develop and specialize. When these receptors are overactive, it can lead to the development of certain cancers, such as Basal Cell Carcinoma and Medulloblastoma. By studying how these receptors work, researchers hope to find new ways to treat these diseases.

Basal Cell Carcinoma

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

Pathological: HealthcareOncology / Skin Cancer

Basal Cell Carcinoma is a common type of skin cancer that starts in the basal cells, which are found in the deepest layer of the epidermis. It typically appears as a pearly or waxy bump and can grow slowly over time. Treatment options include surgery, radiation therapy, and topical medications.

Medulloblastoma

A type of aggressive brain cancer that develops in the cerebellum.

Pathological: HealthcareOncology / Brain Cancer

Medulloblastoma is a malignant tumor that originates in the cerebellum, the part of the brain responsible for balance and coordination. It is most common in children and can spread to other parts of the body. Treatment typically involves surgery, radiation therapy, and chemotherapy.

Simulations

The use of computer models to mimic real-world processes.

Scientific Method: BiotechnologyComputational Biology / Molecular Modeling

Simulations are a powerful tool used in science and engineering to understand complex systems. By creating computer models that represent real-world phenomena, researchers can test hypotheses, explore different scenarios, and gain insights that would be difficult or impossible to obtain through traditional experiments.

Pathogenesis

The development and progression of a disease.

Scientific: PharmaceuticalMedical Research / Disease Mechanisms

Pathogenesis refers to the biological processes that lead to the onset and development of a disease. Understanding the pathogenesis of a particular disease is essential for developing effective treatments.

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 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	7,588,742	143,996	52.70	0 ^hrs 27 ^mins
2	GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti]	Nvidia	GA102	6,928,571	137,765	50.29	0 ^hrs 29 ^mins
3	GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	6,164,143	131,381	46.92	0 ^hrs 31 ^mins
4	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	5,831,365	133,814	43.58	0 ^hrs 33 ^mins
5	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	5,086,506	126,889	40.09	0 ^hrs 36 ^mins
6	GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti]	Nvidia	GA104	4,624,895	122,468	37.76	0 ^hrs 38 ^mins
7	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	4,580,401	122,734	37.32	0 ^hrs 39 ^mins
8	GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate]	Nvidia	GA104	4,512,553	122,677	36.78	0 ^hrs 39 ^mins
9	RTX A5000 GA102GL [RTX A5000]	Nvidia	GA102GL	4,491,302	122,079	36.79	0 ^hrs 39 ^mins
10	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	4,177,421	120,030	34.80	0 ^hrs 41 ^mins
11	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	3,961,178	116,864	33.90	0 ^hrs 42 ^mins
12	GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218	Nvidia	TU104	3,207,614	108,763	29.49	0 ^hrs 49 ^mins
13	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	2,955,053	103,742	28.48	0 ^hrs 51 ^mins
14	GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A]	Nvidia	TU106	2,630,269	102,659	25.62	0 ^hrs 56 ^mins
15	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,310,848	98,300	23.51	1 ^hrs 1 ^mins
16	GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER]	Nvidia	TU106	2,205,788	94,833	23.26	1 ^hrs 2 ^mins
17	GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate]	Nvidia	GA106	2,133,136	95,136	22.42	1 ^hrs 4 ^mins
18	GeForce RTX 2060 12GB TU106 [GeForce RTX 2060 12GB]	Nvidia	TU106	2,091,295	93,007	22.49	1 ^hrs 4 ^mins
19	GeForce RTX 3060 GA106 [GeForce RTX 3060]	Nvidia	GA106	2,085,360	95,319	21.88	1 ^hrs 6 ^mins

20	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	2,021,064	93,809	21.54	1 ^hrs 7 ^mins
21	GeForce GTX 1070 Ti GP104 [GeForce GTX 1070 Ti] 8186	Nvidia	GP104	1,448,406	84,648	17.11	1 ^hrs 24 ^mins
22	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	1,367,249	82,389	16.60	1 ^hrs 27 ^mins
23	GeForce RTX 2060 Mobile / Max-Q TU106M [GeForce RTX 2060 Mobile / Max-Q]	Nvidia	TU106M	1,308,036	81,730	16.00	1 ^hrs 30 ^mins
24	GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632	Nvidia	GM200	1,148,637	77,573	14.81	1 ^hrs 37 ^mins
25	GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463	Nvidia	GP104	1,108,121	77,003	14.39	1 ^hrs 40 ^mins
26	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	1,046,244	74,201	14.10	1 ^hrs 42 ^mins
27	GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]	Nvidia	GA104M	1,009,930	74,243	13.60	1 ^hrs 46 ^mins
28	Tesla M40 GM200GL [Tesla M40] 6844	Nvidia	GM200GL	721,323	65,660	10.99	2 ^hrs 11 ^mins
29	GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372	Nvidia	GP106	586,048	62,846	9.33	2 ^hrs 34 ^mins
30	GeForce GTX 980 GM204 [GeForce GTX 980] 4612	Nvidia	GM204	573,187	61,821	9.27	2 ^hrs 35 ^mins
31	GeForce GTX 970 GM204 [GeForce GTX 970] 3494	Nvidia	GM204	561,219	60,958	9.21	2 ^hrs 36 ^mins
32	GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935	Nvidia	GP106	470,080	57,759	8.14	2 ^hrs 57 ^mins
33	GeForce GTX 1650 TU117 [GeForce GTX 1650]	Nvidia	TU117	418,153	54,022	7.74	3 ^hrs 6 ^mins
34	GeForce GTX 980M GM204 [GeForce GTX 980M] 3189	Nvidia	GM204	325,028	51,443	6.32	3 ^hrs 48 ^mins
35	GeForce GTX 960 GM206 [GeForce GTX 960] 2308	Nvidia	GM206	309,196	50,376	6.14	3 ^hrs 55 ^mins
36	GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138	Nvidia	GP107	301,637	50,062	6.03	3 ^hrs 59 ^mins
37	GeForce GTX 950 GM206 [GeForce GTX 950] 1572	Nvidia	GM206	226,949	45,249	5.02	4 ^hrs 47 ^mins
38	GeForce GTX 770 GK104 [GeForce GTX 770] 3213	Nvidia	GK104	146,194	39,158	3.73	6 ^hrs 26 ^mins
39	GeForce GTX 680 GK104 [GeForce GTX 680] 3250	Nvidia	GK104	125,340	37,364	3.35	7 ^hrs 9 ^mins

40	GeForce GTX 660 Ti GK104 [GeForce GTX 660 Ti] 2634	Nvidia	GK104	98,619	34,528	2.86	8 ^hrs 24 ^mins
41	GeForce GTX 660 GK106 [GeForce GTX 660]	Nvidia	GK106	68,000	30,496	2.23	10 ^hrs 46 ^mins
42	Quadro K1200 GM107GL [Quadro K1200]	Nvidia	GM107GL	50,936	27,725	1.84	13 ^hrs 4 ^mins
43	GTX 650 Ti Boost GK106 [GTX 650 Ti Boost]	Nvidia	GK106	43,041	22,243	1.94	12 ^hrs 24 ^mins
44	GeForce GT 730 GK208B [GeForce GT 730] 692.7	Nvidia	GK208B	15,400	16,800	0.92	26 ^hrs 11 ^mins

Research: CANCER Folding Project #14932

Project Summary AI Beta

Project team

Work unit

Official Project Description

Hardware Performance for Project 14932

GPU PPD Averages

Research: CANCER Folding Project #14932

Project Summary AI Beta

Project team

Work unit

Related projects

GPU PPD Averages