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...

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...

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

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...

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...

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...

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...

This dataset presents land surface parameters designed explicitly for global kilometer-scale Earth system modeling and has significant implications for enhancing our understanding of water, carbon, and energy cycles in the context of global change. Specifically, it includes four categories of...

Inclusion levels of alternative splicing (AS) events of five different varieties (i.e. skipped exon (SE), retained intron (RI), alternative 5’ splice site (A5SS), alternative 3’ splice site (A3SS), and mutually exclusive exons (MXE)) were measured in human blood samples from two separate cohorts of...

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...

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 --...