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David Degnan is a biological data scientist who develops bioinformatic and statistical pipelines for multi-omics data, specifically the fields of proteomics, metabolomics, and multi-omics (phenotypic) data integration. He has experience with top-down & bottom-up proteomics analysis, genomics &...

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)...

Washington State University Distinguished Graduate Research Program Program: Chemical Engineering WSU-PNNL Advisor: Aaron Wright

Comprised of 6,426 sample runs, The Environmental Determinants of Diabetes in the Young (TEDDY) proteomics validation study constitutes one of the largest targeted proteomics studies in the literature to date. Making quality control (QC) and donor sample data available to researchers aligns with...

Federal and state decarbonization goals have led to numerous financial incentives and policies designed to increase access and adoption of renewable energy systems. In combination with the declining cost of both solar photovoltaic and battery energy storage systems and rising electric utility rates...

PNNL’s Vision Statement for Equity in the Power Grid Drawing from a wealth of interdisciplinary research in grid modernization, PNNL is spearheading an effort to advance equity and energy justice through the role of scientific research with the goal of building an advanced national power grid...

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This data is supplementary to the manuscript Expanding the access of wearable silicone wristbands in community-engaged research through best practices in data analysis and integration by Lisa M. Bramer, Holly M. Dixon, David J. Degnan, Diana Rohlman, Julie B. Herbstman, Kim A. Anderson, and Katrina...

Extreme weather events, including fires, heatwaves(HWs), and droughts, have significant impacts on earth, environmental, and power energy systems. Mechanistic and predictive understanding, as well as probabilistic risk assessment of these extreme weather events, are crucial for detecting, planning...

As energy prices rise and climate change brings more extreme and frequent days of heating and cooling, households must allocate more of their income to energy bills, increasing their energy burden. Many strategies are employed to alleviate high energy burden, such as weatherization, energy...

A total of 172 children from the DAISY study with multiple plasma samples collected over time, with up to 23 years of follow-up, were characterized via proteomics analysis. Of the children there were 40 controls and 132 cases. All 132 cases had measurements across time relative to IA. Sampling was...

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...

The presentation and supporting information provide data on the performance of an engineering-scale cross-flow heat exchanger used in hydrothermal liquefaction (HTL). Temperature profiles are provide for the process of waste water treatment sludges and a food waste. The data can be used to model...

Supporting data and code uploaded to DataHub for "How do the weather regimes drive wind speed and power production at the sub-seasonal to seasonal timescales over the CONUS?" Created by Ye Liu*, Sha Feng*, Yun Qian, Berg K Larry, Huilin Huang *POC: Ye Liu, Ye.Liu@pnnl.gov Sha Feng, sfeng@pnnl.gov --...

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This dataset includes one baseline and three cybersecurity based scenarios utilizing the IEEE 9 Bus Model. This instantiation of the IEEE 9 model was built utilizing the OpalRT Simulator ePhasorsim module, with Bus 7 represented by hardware in the loop (HiL). The HiL was represented by two SEL351s...

ProxyTSPRD profiles are collected using NVIDIA Nsight Systems version 2020.3.2.6-87e152c and capture computational patterns from training deep learning-based time-series proxy-applications on four different levels: models (Long short-term Memory and Convolutional Neural Network), DL frameworks...