This data set provides the 16S microbial community composition via DNA and cDNA sequence analyses at the time of peat coring for Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2014-2017 from the Spruce and Peatlands Under Changing Environments (SPRUCE). Samples were extracted using a...
Filter results
Category
- (-) Microbiome Science (43)
- (-) Computational Mathematics & Statistics (7)
- (-) Visual Analytics (6)
- (-) Ecosystem Science (4)
- (-) Grid Cybersecurity (2)
- Scientific Discovery (310)
- Biology (201)
- Earth System Science (136)
- Human Health (104)
- Integrative Omics (74)
- Computational Research (25)
- National Security (22)
- Computing & Analytics (15)
- Chemistry (10)
- Energy Resiliency (10)
- Data Analytics & Machine Learning (9)
- Materials Science (7)
- Chemical & Biological Signatures Science (5)
- Renewable Energy (5)
- Weapons of Mass Effect (5)
- Atmospheric Science (4)
- Coastal Science (4)
- Data Analytics & Machine Learning (4)
- Plant Science (3)
- Cybersecurity (2)
- Distribution (2)
- Electric Grid Modernization (2)
- Energy Efficiency (2)
- Energy Storage (2)
- Solar Energy (2)
- Bioenergy Technologies (1)
- Computational Mathematics & Statistics (1)
- Grid Analytics (1)
- High-Performance Computing (1)
- Subsurface Science (1)
- Terrestrial Aquatics (1)
- Transportation (1)
- Wind Energy (1)
Tags
- Omics (10)
- PerCon SFA (9)
- High Throughput Sequencing (8)
- Genomics (7)
- Sequencer System (5)
- Synthetic Biology (5)
- Mass Spectrometry (4)
- A. pittii SO1 (2)
- Amplicon Sequencing (2)
- Biological and Environmental Research (2)
- Chitin (2)
- Cybersecurity (2)
- Electrical energy (2)
- Imaging (2)
- Long Read Sequencer (2)
- Machine Learning (2)
- Mass Spectrometer (2)
- Mass spectrometry data (2)
- Proteomics (2)
- RNA Sequence Analysis (2)
- Soil (2)
- Sorghum bicolor (2)
- Spectroscopy (2)
- Statistical Expression Analysis (2)
- Whole Genome Sequencing (2)
- DOE (1)
- Lipidomics (1)
- metabolomics (1)
- Output Databases (1)
- ToF-SIMS (1)
This data set provides the 16S microbial community composition of peat and sand ingrowth cores via DNA and cDNA sequence analysis before and during Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2015-2016 from the Spruce and Peatlands Under Changing Environments (SPRUCE). Samples were...
Category
This data set provides ITS fungal community composition via DNA and cDNA sequence analysis at the time of peat coring for Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2014-2017 from the Spruce and Peatlands Under Changing Environments (SPRUCE). Samples were extracted using a Qiagen...
Category
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...
This data set provides the ingrowth peat extracellular enzyme potential (EE) for before and during Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2015-2016 from the Spruce and Peatlands Under Changing Environments (SPRUCE). EE potential was quantified and calculated following a...
Category
This data set provides the ingrowth peat extracellular enzyme potential (EE) for before and during Deep Peat Heating (DPH) and Whole Ecosystem Warming (WEW) for 2015-2016 from the Spruce and Peatlands Under Changing Environments (SPRUCE). EE potential was quantified and calculated following a...
Category
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...
Please cite as : McClure R.S., Y. Farris, R.E. Danczak, W.C. Nelson, H. Song, A. Kessler, and J. Lee, et al. 2022. 16s data from MSC-2 growth. [Data Set] PNNL DataHub. https://data.pnnl.gov/group/nodes/dataset/33231 16s data from MSC-2 growth 3 fastq of 16s amplicon data of MSC2 1 csv file of raw...
Category
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...
Category
Last updated on 2023-03-21T18:35:22+00:00 by LN Anderson SAGE-RTP RT-PCR Amplicon Sequencing Barcode Count Analysis Promoter expression data for five bacterial species associated with the Serine recombinase Assisted Genome Engineering (SAGE) research project. Raw Measurement Data NCBI BioProject...
Last updated on 2023-05-31T16:35:53+00:00 by LN Anderson PerCon SFA: Sequencing of Sorgoleone Promoting Rhizobacteria Isolates Whole genome sequencing (WGS) of sorgoleone utilizing rhizobacteria strains Pseudomonas sorgoleonovorans SO81 , Burkholderia anthina SO82 , and Acinetobacter pittii SO1 , as...
Last updated on 2024-04-19T19:12:08+00:00 by LN Anderson PerCon SFA: Profiling sorghum-microbe interactions with a specialized photoaffinity probe identifies key sorgoleone binders in Acinetobacter pitti Mass spectrometry-based global proteome analysis and SoDA-PAL photoaffinity probe labeled...
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...
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...
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...