"Visualizing the Hidden Half: Plant-Microbe Interactions in the Rhizosphere" Plant roots and the associated rhizosphere constitute a dynamic environment that fosters numerous intra- and interkingdom interactions, including metabolite exchange between plants and soil mediated by root exudates and the...
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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)...
Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson PerCon SFA Project Publication Experimental Data Catalog The Persistence Control of Engineered Functions in Complex Soil Microbiomes Project (PerCon SFA) at Pacific Northwest National Laboratory ( PNNL ) is a Genomic Sciences Program...
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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.
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1
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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Last updated on 2024-03-03T02:26:52+00:00 by LN Anderson The Thermo Scientific™ Q Exactive™ Plus Mass Spectrometer benchtop LC-MS/MS system combines quadruple precursor ion selection with high-resolution, accurate-mass (HRAM) Orbitrap detection to deliver exceptional performance and versatility...
The Thermo Scientific™ Q Exactive™ GC hybrid quadrupole Orbitrap Mass Spectrometer provides an unmatched combination of sensitivity, mass-accuracy and resolving power in a single analysis for the highest confidence in compound discovery, identification, and quantitation. With best-in-class...
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Last updated on 2024-03-03T02:26:52+00:00 by LN Anderson The Thermo Scientific™ Velos Pro™ Orbitrap Mass Spectrometer instrument data source combines advanced mass accuracy with an ultra-high resolution Orbitrap mass analyzer for increased sensitivity, enabling molecular weight determination for...