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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...

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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 .

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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...

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Earth Scientist Emily Graham is an quantitative ecosystem ecologist in the Biological Sciences Group at PNNL and is part of the Ecosystem Science Team. She is co-principal investigator of the Subsurface Biogeochemical Research Science Focus Area (SFA) and a key member of PNNL’s soil microbiome SFA...
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 IONTOF TOF.SIMS 5 data source is a time-of-flight secondary ion mass spectrometer and powerful surface analysis tool used to investigate scientific questions in biological, environmental, and energy research. Among the most sensitive of surface analysis tools, it uses a high-vacuum technique...

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...

Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. Metatranscriptomic data from MSC-2. [Data Set] PNNL DataHub. https://data.pnnl.gov/group/nodes/dataset/33232 Metatranscriptomic data from MSC-2 12 fastq files (6 forward read, 6 reverse...

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...

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...

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...