Complete replicate terabase metagenome (TmG.2.0) of grassland soil microbiome collections from KPBS field site in Manhattan, KS. Metagenome (unclassified soil sequencing) Data DOI Package, version 2.0.

Complete replicate terabase metagenome (TmG.2.0) of grassland soil microbiome collections from COBS field site in Boone County, IA. Metagenome (unclassified soil sequencing) Data DOI Package, version 2.0.

Complete replicate terabase metagenome (TmG.2.0) of grassland soil microbiome collections from IAREC field site in Prosser, WA. Metagenome (unclassified soil sequencing) Data DOI Package, version 2.0.

HDF5 file containing 10,000 hydraulic transmissivity inputs and the corresponding hydraulic pressure field outputs for a two-dimensional saturated flow model of the Hanford Site. The inputs are generated by sampling a 1,000-dimensional Kosambi-Karhunen-Loève (KKL) model of the transmissivity field...

This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities.

This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities.

This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities. This data was generated by PNNL. Activities can be phone calls, transactions, or any other type of communications. Most of...

The VAST Challenge 2019 presents three mini-challenges and a grand challenge for you to apply your visual analytics research and technologies to help a city grapple with the aftermath of an earthquake that damages their nuclear power plant. These challenges are open to participation by individuals...

The Biomedical Resilience & Readiness in Adverse Operating Environments (BRAVE) Project develop new capabilities to improve health and performance of first responders in adverse operating environments common to national defense. The BRAVE project analyze biological samples, collect physiological...

Machine learning is a core technology that is rapidly advancing within type 1 diabetes (T1D) research. Our Human Islet Research Network (HIRN) grant is studying early cellular response initiating β cell stress in T1D through the generation of heterogenous low- and high-throughput molecular...

The Environmental Determinants of Diabetes in the Young (TEDDY) study is searching for factors influencing the development of type 1 diabetes (T1D) in children. Research has shown that there are certain genes that correlate to higher risk of developing T1D, but not all children with these genes...

The Diabetes Autoimmunity Study in the Young (DAISY) seeks to find environmental factors that can trigger the development of type 1 diabetes (T1D) in children. DAISY follows children with high-risk of developing T1D based on family history or genetic markers. Genes, diets, infections, and...

Biography Ernesto Nakayasu is a senior research scientist focused on understanding molecular mechanisms of diseases. Nakayasu has been applying systems biology and mass spectrometry-based omics measurements to study how pathogens and metabolic alterations cause human diseases; the goal is to...