High-Performance Computing. Training. High-Speed Networking.
Transferring Data from Box
If you have data on Box, you can learn how to transfer it to SCINet resources by watching this instructional video or by following the instructions in the SCINet User Guides.
What is SCINet?
The SCINet initiative is an effort by the USDA Agricultural Research Service (ARS) to grow USDA’s research capacity by providing scientists with access to high-performance computing clusters, high-speed networking for data transfer, and training in scientific computing.
Upcoming Trainings and Events
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Managing data with Globus
The SCINet Office will be hosting a webinar on managing data with Globus. We will demonstrate how to:
- Log in to Globus using your SCINet account.
- Access directories and files on SCINet systems (supercomputers and long-term storage).
- Transfer files among SCINet systems and to and from SCINet systems and local storage.
- Set up recurring data transfers and synchronize local and remote directories.
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Automate your SCINet pipeline with Snakemake
Snakemake is a popular workflow management tool that can help organize, document, scale, run, and reproduce your workflows. Snakemake workflows are described via a human-readable, Python-based language, and can be integrated into SCINet high-performance computing (HPC) clusters via Slurm and Conda.
In this workshop, Aaron Yerke (SCINet/AI-COE fellow) will introduce the basics of a Snakemake workflow and demonstrate how to run it on a SCINet cluster. After attending this workshop, you should be able to integrate Snakemake into your own projects on SCINet HPC clusters.
Featured Stories
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Comparative genomics reveals a light-activated phytotoxin that contributes to red leaf blotch disease of soybean
*Coniothyrium glycines* causes red leaf blotch, a major disease of soybean in Africa (Figure 1). It is one of two fungal pathogens listed on the USDA APHIS Plant Protection and Quarantine Select Agents and Toxins list owing to its likely destructive potential if it spreads to major soybean growing regions.
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High-Performance Computing Facilitates Improved Understanding of Phenotypic Plasticity in Maize
In maize and other crops, important traits are often complex, affected by genetics, the environment, and their interaction. In addition, different crop varieties exhibit varying degrees of phenotypic plasticity, in which a given genotype displays different phenotype values in different environments.
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SCINet as a Resource for Safeguarding and Advancing ARS's Biological Collections
Across the USDA’s Agricultural Research Service (ARS) there are nealy 100 biological collections containing millions of preserved and viable specimens including animal tissues, seeds, fungal cultures, plant accessions, pinned insects, and viral isolates. These specimens and the data about them document and support ARS research efforts and are an integral part of delivering on the Agency’s mission.
Find out how SCINet can enable your research
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Working Groups
Information about how our collaborators currently use SCINet
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Fellowship Opportunities
SCINet-funded research fellowship opportunities for PhD and MS level graduates
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How to Use SCINet
Quick Start guide to getting up and running with SCINet
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Running Analyses
Guides for running different analyses
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Frequently Asked Questions
Answers to common questions asked about SCINet
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Need Help?
Find who you need to contact for specific issues or requests