Showing 1 - 15 of 27
Dataset

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.

Dataset

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.

Dataset

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.

Viral communities detected from three large grassland soil metagenomes with historically different precipitation moisture regimes.

A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery...

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.

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Fusarium sp. DS682 Proteogenomics Statistical Data Analysis of SFA dataset download: 10.25584/KSOmicsFspDS682/1766303 . GitHub Repository Source: https://github.com/lmbramer/Fusarium-sp.-DS-682-Proteogenomics MaxQuant Export Files (txt) Trelliscope Boxplots (jsonp) Fusarium Report (.Rmd, html)...

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.

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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...
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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...
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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...

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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...

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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...

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This data was generated by the organization IvySys. Activities can be phone calls, transactions, or any other type of communications. Most of the files are of the type .edges, .rdf, or .csv; but all can be opened in a text editor. A good introduction to this data can be found in \Tutorial1\MAA...