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- https://www.materialsdatafacility.org/
- http://matsci.registry.nationaldataservice.org/
- http://nist.registry.nationaldataservice.org
- http://bipm.registry.nationaldataservice.org
- http://mgi.registry.nationaldataservice.org:8181/ (Materials Resource Registry)
- https://trial.publish.globus.org/ (Clowder instance following master branch)
- http://petrel.alcf.anl.gov/ (Clowder instance following current development branch, feature/CATS-224-ability-to-launch-vm-from-dataset)
- https://trello.com/b/lmDf7NDa/materials-data-facility (Issue tracker)
- http://wiki.nationaldataservice.org/MaterialsMetadataTerms (Metadata)
- Globus endpoints: ncsa#mdf (141.142.208.128),
ncsa#mdf-publish (141.142.193.28) - Team Resources
NSF Midwest BigData Hub
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- http://midwestbigdatahub.org/Globus endpoints: ncsa#mdf (141.142.208.128),
ncsa#mdf-publish (141.142.193.28)
iSEE Plants in silico
As the Earth’s population climbs toward 9 billion by 2050 — and the world climate continues to change, affecting temperatures, weather patterns, water supply, and even the seasons — future food security has become a grand world challenge. Accurate prediction of how food crops react to climate change will play a critical role in ensuring food security. An ability to computationally mimic the growth, development and response of plants to the environment will allow researchers to conduct many more experiments than can realistically be achieved in the field. Designing more sustainable crops to increase productivity depends on complex interactions between genetics, environment, and ecosystem. Therefore, creation of an in silico — computer simulation — platform that can link models across different biological scales, from cell to ecosystem level, has the potential to provide more accurate simulations of plant response to the environment than any single model could alone.
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