Friction Stir Welding Processing Friction Stir Welding (FSW) is a solid-phase joining process achieved by spinning a tool and plunging it into the weld site. Frictional heating and material deformation enable the formation of a plasticized region below the tool shoulder called the stir-zone. The FSW...

Please cite as : Authors. Year. PNNL MCPC Characterization Round 1. [Data Set] PNNL DataHub. DOI This data is published under a CC0 license . The authors encourage data reuse and request attribution by referencing the above citations for the data package. Principal Researcher: Dr. Erin Barker...

Please cite as : Authors. Year. PNNL MCPC Characterization Round 3. [Data Set] PNNL DataHub. DOI This data is published under a CC0 license . The authors encourage data reuse and request attribution by referencing the above citations for the data package. Principal Researcher: Dr. Erin Barker...

Please cite as : Authors. Year. PNNL MCPC Characterization Round 2. [Data Set] PNNL DataHub. DOI This data is published under a CC0 license . The authors encourage data reuse and request attribution by referencing the above citations for the data package. Principal Researcher: Dr. Erin Barker...

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...

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...

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...

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...

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...

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...

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...

Predictive Phenomics Initiative (PPI) Project Data Catalog Collection The Predictive Phenomics Initiative (PPI) is an internal LDRD investment at Pacific Northwest National Laboratory focused on unraveling the mysteries of molecular function in complex biological systems. Explore PPI research...

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 &...

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...

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...