RESEARCH: PARASITIC WEED
FOLDING PROJECT #18901 PROFILE
PROJECT TEAM
Manager(s): Jiming ChenInstitution: University of Illinois at Urbana-Champaign
WORK UNIT INFO
Atoms: 38,594Core: OPENMM_22
Status: Public
Related Projects
TLDR; PROJECT SUMMARY AI BETA
Parasitic weeds like Striga cause billions of dollars in crop damage each year. They use a chemical signal from host plants called strigolactone to grow. The project aims to understand how these weeds sense this signal so we can develop new ways to stop them.
Note: This TLDR is a simplication and may not be 100% accurate.OFFICAL PROJECT DESCRIPTION
Hormone signaling in parasitic weeds Parasitic weeds such as Striga destroy ~$10 billion worth of food crops worldwide every year.
Their seeds can lie dormant in the soil for years and germinate when it detects a chemical signal from host plants called strigolactone.
Additionally, the receptor proteins that perceive strigolactone are several orders of magnitude more sensitive than the ones found in host plants, meaning they can induce signaling at much lower levels of strigolactone.
This series of project aims to provide molecular insight into the strigolactone signaling process to facilitate the design of agrochemicals that can be used to combat parasitic weeds.
RELATED TERMS GLOSSARY AI BETA
Hormone
Chemical messengers that regulate plant growth and development.
Hormones are essential signaling molecules in plants. They control various processes like growth, flowering, fruit ripening, and responses to environmental stimuli. Different hormones have specific functions, and their interactions create a complex regulatory network.
Signal
Information transmitted between cells or organisms.
Signals are essential for communication and coordination in living systems. They can be chemical (like hormones), electrical, or mechanical. Signal transduction is the process by which signals are received, processed, and ultimately lead to a specific response.
Strigolactone
A class of plant hormones that regulate growth and development.
Strigolactones are a group of plant hormones involved in various processes like branching, root development, and interactions with symbiotic fungi. They also play a crucial role in parasitic weed germination by acting as chemical signals for the parasite.
Receptor
A protein that binds to a specific molecule (ligand) and initiates a cellular response.
Receptors are essential components of signal transduction pathways. They recognize and bind to specific signaling molecules (ligands), triggering a cascade of events within the cell. This ultimately leads to a specific cellular response, such as gene expression or changes in protein activity.
Germination
The process of a seed sprouting and developing into a seedling.
Germination is the critical stage in a plant's life cycle where a dormant seed awakens and begins to grow. It involves various physiological changes, including water absorption, enzyme activation, and the emergence of roots and shoots.
PROJECT FOLDING PPD AVERAGES BY GPU
Data as of Sunday, 26 April 2026 03:27:08|
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 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 6,061,398 | 153,326 | 39.53 | 0 hrs 36 mins |
| 2 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 4,293,266 | 61,962 | 69.29 | 0 hrs 21 mins |
| 3 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 4,221,538 | 59,387 | 71.09 | 0 hrs 20 mins |
| 4 | GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448 |
Nvidia | TU102 | 3,614,447 | 58,567 | 61.71 | 0 hrs 23 mins |
| 5 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 3,516,965 | 56,550 | 62.19 | 0 hrs 23 mins |
| 6 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 3,302,428 | 53,703 | 61.49 | 0 hrs 23 mins |
| 7 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,185,405 | 55,302 | 57.60 | 0 hrs 25 mins |
| 8 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 2,951,388 | 54,655 | 54.00 | 0 hrs 27 mins |
| 9 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 2,874,621 | 53,537 | 53.69 | 0 hrs 27 mins |
| 10 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 2,546,408 | 51,534 | 49.41 | 0 hrs 29 mins |
| 11 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 2,434,398 | 50,179 | 48.51 | 0 hrs 30 mins |
| 12 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 2,236,882 | 43,914 | 50.94 | 0 hrs 28 mins |
| 13 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,193,869 | 49,054 | 44.72 | 0 hrs 32 mins |
| 14 | GeForce RTX 3060 Ti GA104 [GeForce RTX 3060 Ti] |
Nvidia | GA104 | 1,998,839 | 48,583 | 41.14 | 0 hrs 35 mins |
| 15 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 1,971,697 | 45,084 | 43.73 | 0 hrs 33 mins |
| 16 | GeForce RTX 2080 Mobile TU104M [GeForce RTX 2080 Mobile] |
Nvidia | TU104M | 1,793,284 | 45,662 | 39.27 | 0 hrs 37 mins |
| 17 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 1,679,823 | 45,342 | 37.05 | 0 hrs 39 mins |
| 18 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 1,419,319 | 42,296 | 33.56 | 0 hrs 43 mins |
| 19 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,342,803 | 41,694 | 32.21 | 0 hrs 45 mins |
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|||||||
| 20 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 1,206,890 | 40,509 | 29.79 | 0 hrs 48 mins |
| 21 | GeForce GTX 1660 Ti TU116 [GeForce GTX 1660 Ti] |
Nvidia | TU116 | 1,087,669 | 39,025 | 27.87 | 0 hrs 52 mins |
| 22 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,087,074 | 38,573 | 28.18 | 0 hrs 51 mins |
| 23 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,066,165 | 38,643 | 27.59 | 0 hrs 52 mins |
| 24 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 910,585 | 35,192 | 25.87 | 0 hrs 56 mins |
| 25 | GeForce GTX 1060 6GB GP106 [GeForce GTX 1060 6GB] 4372 |
Nvidia | GP106 | 880,918 | 36,705 | 24.00 | 1 hrs 0 mins |
| 26 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 677,324 | 32,925 | 20.57 | 1 hrs 10 mins |
| 27 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 601,656 | 32,033 | 18.78 | 1 hrs 17 mins |
| 28 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 460,165 | 29,112 | 15.81 | 1 hrs 31 mins |
| 29 | GeForce GTX 970 GM204 [GeForce GTX 970] 3494 |
Nvidia | GM204 | 442,672 | 28,691 | 15.43 | 1 hrs 33 mins |
| 30 | GeForce GTX 1650 TU117 [GeForce GTX 1650] |
Nvidia | TU117 | 357,873 | 26,672 | 13.42 | 1 hrs 47 mins |
| 31 | GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138 |
Nvidia | GP107 | 336,416 | 26,184 | 12.85 | 1 hrs 52 mins |
| 32 | GeForce GTX 980M GM204 [GeForce GTX 980M] 3189 |
Nvidia | GM204 | 336,391 | 26,475 | 12.71 | 1 hrs 53 mins |
| 33 | P106-090 GP106 [P106-090] |
Nvidia | GP106 | 324,724 | 25,932 | 12.52 | 1 hrs 55 mins |
| 34 | GeForce GTX 950 GM206 [GeForce GTX 950] 1572 |
Nvidia | GM206 | 211,339 | 22,405 | 9.43 | 2 hrs 33 mins |
| 35 | Quadro P1000 GP107GL [Quadro P1000] |
Nvidia | GP107GL | 172,436 | 21,244 | 8.12 | 2 hrs 57 mins |
| 36 | GeForce GTX 760 GK104 [GeForce GTX 760] 2258 |
Nvidia | GK104 | 72,242 | 15,970 | 4.52 | 5 hrs 18 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
Data as of Sunday, 26 April 2026 03:27:08|
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
|---|