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...

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...

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 .

Coastal landscapes are increasingly exposed to seawater due to sea level rise and extreme weather events. The biogeochemical responses of these vulnerable ecosystems are poorly understood, limiting our ability to predict how their role in global biogeochemical cycles will shift under future...

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...

This dataset contains time series data collected from devices and sensors in the PNNL Systems Engineering Building collected using the VOLTTRON platform. The data includes readings from HVAC, power, and lighting systems and was collected between March and July of 2018. This work was funded by the...

The year 2014 solution files are based on model calibration effort based on inputs and data from Year 2014 as described in Khangaonkar et al. 2018). It includes water surface elevation, currents, temperature and salinity at an hourly interval. These netcdf files with 24 hourly records include...

The year 2014 solution files are based on model calibration effort based on inputs and data from Year 2014 as described in Khangaonkar et al. 2018). It includes water surface elevation, currents, temperature and salinity at an hourly interval. These netcdf files with 24 hourly records include...

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...

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...

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 --...