Showing 16 - 30 of 37

Predictive Phenomics is addressing the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems .

  1. Datasets

    0

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...

  1. 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...

  1. Datasets

    3

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...

  1. Datasets

    2
The Biomedical Resilience & Readiness in Adverse Operating Environments (BRAVE) Project develop new capabilities to improve health and performance of first responders in adverse operating environments common to national defense. The BRAVE project analyze biological samples, collect physiological...
  1. Datasets

    1
Washington State University Distinguished Graduate Research Program Program: Chemical Engineering WSU-PNNL Advisor: Aaron Wright
Sara Gosline received BA in Computer Science from Columbia University and spent two years working in software before returning to graduate school full time. She received her Masters and PhD in Computer Science from McGill University with a specialty in Bioinformatics and then moved to the...

Biography Kelly is a senior data scientist in the Computational Biology group within the Biological Sciences Division at Pacific Northwest National Laboratory (PNNL). After earning a MS in Biostatistics from the University of Washington in 2012, she worked at a cancer research company for two years...

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 &...

The EyeSea underwater video dataset was assembled for developing algorithms for detecting fish in real world underwater video data. The data were recorded as part of environmental monitoring efforts at three different water power sites. The Ocean Renewable Power Company (ORPC) data were recorded in...

Comprehensive assessment of climate datasets created by statistical or dynamical models is important for effectively communicating model projection and associated uncertainty to stakeholders and decision-makers. The Department of Energy FACETS project aims to foster such communication through...

Biomedical Resilience & Readiness in Adverse Operating Environments (BRAVE) Project: Exhaled Breath Condensate (EBC) TMT Proteomic Transformation Data Exhaled breath condensate (EBC) represents a low-cost and non-invasive means of examining respiratory health. EBC has been used to discover and...

The dataset consists of model outputs (CLM45BGC, CLM5BGC, and CLM5SP) There are three CLM simulations associated with Cheng et al. 2020, namely CLM4.5 in biogeochemistry mode (CLM45BGC), CLM5 in biogeochemistry mode (CLM5BGC), and CLM5in satellite phenology mode (CLM5SP). The monthly, daily and...

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...

This dataset includes the results of high-fidelity, hardware in the loop experimentation on simulated models of representative electric and natural gas distribution systems with real cyber attack test cases. Such datasets are extremely important not only in understanding the system behavior during...