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This project is an interdisciplinary collaboration supported by US DOE Office of Science's Scientific Discovery through Advanced Computing (SciDAC) program. The project addresses a crucial but largely overlooked source of error in the Energy Exascale Earth System Model (E3SM) and other atmosphere...
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.
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...
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 Illumina MiSeq System Sequencer is a high-throughput DNA sequencer machine developed and manufactured by Illumina , and is designed for sequencing data acquisition using synthesis technology to provide an end-to-end solution (cluster generation, amplification, sequencing, and data analysis) in a...
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...