High-Performance Computing. Training. High-Speed Networking.
Learn MoreAtlas Update
There have been several changes to the Atlas compute cluster. Read more about these updates here.
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
-
SCINet Corner · Data Visualization: R packages
The SCINet Corner is a recurring virtual gathering to provide a space for people to meet and discuss SCINet-related items.
-
ISU · Genome Assembly Workshop
In this interactive, hands-on workshop, you will learn how to use SCINet’s computing resources to convert raw DNA sequencing data into a complete genome assembly. Along the way, you will also learn best practices for ensuring that your genome assemblies are robust and useful for downstream analyses.
-
SCINet Corner · Data Visualization: Python packages
The SCINet Corner is a recurring virtual gathering to provide a space for people to meet and discuss SCINet-related items.
Featured Stories
-
CameraTrapDetectoR: Detecting, Classifying and Counting Animals in Camera Trap Images
The use of camera traps is a popular and cost-effective way to monitor animal populations, evaluate animal behavior, and study ecological processes influencing populations. However, a camera trap dataset for a single site or research question can result in millions of images that require classification to be useful for analysis.
-
Cattle Genome, Pangenome, Annotation, and FarmGTEx
FarmGTEx Consortium aims to create a comprehensive public resource for studying tissue-specific gene expression and regulation in major livestock species, including cattle, pigs, sheep, goats, and chickens.
-
A Machine Learning Tool to Collapse Diet or Microbiome Data Using Taxonomic Structure
Researchers at the USDA-ARS Western Human Nutrition Research Center (WHNRC) are leveraging machine learning to uncover the molecular underpinnings of diet’s association with health.
Find out how SCINet can enable your Research
-
Working Groups
Information about how our collaborators currently use SCINet
-
Fellowship Opportunities
SCINet-funded research fellowship opportunities for PhD and MS level graduates
-
How to Use SCINet
Quick Start guide to getting up and running with SCINet
-
Running Analyses
Guides for running different analyses
-
Frequently Asked Questions
Answers to common questions asked about SCINet
-
Contact Us
Find who you need to contact for specific issues or requests