The srpAnalytics modeling pipeline for the Superfund Research Program Analytics Portal.

Code pertaining to the Soil Microbiome SFA Project publication data visualizations 'DNA viral diversity, abundance and functional potential vary across grassland soils with a range of historical moisture regimes' for processing publication data downloads.

Data Science & Biostatistics

Dr. Paul Piehowski is the Proteomics team leader for PNNL’s Environmental and Molecular Sciences Division and the Environmental Molecular Sciences Laboratory (EMSL) user program. Piehowski is an analytical chemist whose research is focused on the application of mass spectrometry to biological...

Dr. Gao obtained her Ph.D degree in Chemistry from institute of chemistry, Chinese Academy of Science. His Ph.D research focused on multiscale modeling of morphology and properties of polymeric materials, polymer processing and unveiling the process–properties relationships. (atomic to coarse...

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...

The influence of tidal inundation dynamics on below ground carbon pools is poorly understood across coastal terrestrial-aquatic interface (TAI) ecosystems. The dynamic environmental conditions of tidally-influenced landscapes, the chemically complex nature of carbon compounds, the diverse nature of...

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...

The following R source code was used for plotting figures of the viral communities detected from three grasslands soil metagenomes with a historical precipitation gradient ( WA-TmG.2.0 , KS-TmG.2.0 , IA-TmG.2.0 ) from project publication 'DNA viral diversity, abundance and functional potential vary...

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)...

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 long-term goals of this scientific focus area (SFA) are to develop flexible and extensible modeling capabilities that capture the dynamic multiscale interactions among climate, energy, water, land, socioeconomics, critical infrastructure, and other sectors and to use these capabilities to study...

Some of the most rapid environmental changes on the planet are experienced in high-latitude regions. These changes affect all Earth system components, including the ocean, atmosphere, cryosphere, and marine and terrestrial ecosystems, and have both regional and global implications. The main...