"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...
Showing 1 - 9 of 9
The theoretical prediction of x-ray absorption spectra (XAS) has become commonplace in electronic structure theory. The ability to better model and understand L-edge spectra is of great interest in the study of transition metal complexes and a wide variety of solid state materials. However, until...
Publication
The recently developed real-time nuclear–electronic orbital (RT-NEO) approach provides an elegant framework for treating electrons and selected nuclei, typically protons, quantum mechanically in nonequilibrium dynamical processes. However, the RT-NEO approach neglects the motion of the other nuclei...
Predicting accurate nuclear magnetic resonance chemical shieldings relies upon cancellation of different types of errors between the theoretically calculated shielding constant of the analyte of interest and the reference. Often, the intrinsic error in computed shieldings due to basis sets...
The Human Islet Research Network (HIRN) is a large consortia with many research projects focused on understanding how beta cells are lost in type 1 diabetics (T1D) with a goal of finding how to protect against or replace the loss of functional beta cells. The consortia has multiple branches of...
Datasets
0
Project
The Phenotypic Response of the Soil Microbiome to Environmental Perturbations Project (Soil Microbiome SFA) at Pacific Northwest National Laboratory is a Genomic Sciences Program Science Focus Area (SFA) Project operating under the Environmental Microbiome Science Research Area. The Soil Microbiome...
Datasets
23
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...
Datasets
1
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...
Datasets
1
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...
Datasets
3
