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Software
EyeSea software is available at https://github.com/pnnl/EyeSea

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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pmartR Software Overview The pmartR package provides a single software tool for QC (filtering and normalization), exploratory data analysis (EDA), and statistical analysis (robust to missing data) and includes numerous visualization capabilities of mass spectrometry (MS) omics data (proteomic...

Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson Snekmer: A scalable pipeline for protein sequence fingerprinting using amino acid recoding (AAR) Snekmer is a software package designed to reduce the representation of protein sequences by combining amino acid reduction (AAR) with the kmer...

The influence of tidal inundation dynamics on below ground carbon pools is poorly understood across coastal terrestrial-aquatic interface (TAI) ecosystems. The dynamic environmental conditions of tidally-influenced landscapes, the chemically complex nature of carbon compounds, the diverse nature of...

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The Phenotypic Response of the Soil Microbiome to Environmental Perturbations Project (Soil Microbiome SFA) at Pacific Northwest National Laboratory is a Genomic Sciences Program Science Focus Area (SFA) Project operating under the Environmental Microbiome Science Research Area. The Soil Microbiome...

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This dataset was collected from PNNL operated buildings utilizing the PNNL developed open source platform, VOLTTRON in conjunction with PNNL Facilities and Operations staff. VOLTTRON provides an environment for buildings researchers to deploy applications interacting with building management systems...
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The long-term goals of this scientific focus area (SFA) are to develop flexible and extensible modeling capabilities that capture the dynamic multiscale interactions among climate, energy, water, land, socioeconomics, critical infrastructure, and other sectors and to use these capabilities to study...
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This project is an interdisciplinary collaboration supported by US DOE Office of Science's Scientific Discovery through Advanced Computing (SciDAC) program. The project addresses a crucial but largely overlooked source of error in the Energy Exascale Earth System Model (E3SM) and other atmosphere...

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The Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) database was generated to mechanistically understand how feedbacks across scales, from molecular to plant to plant populations and communities to ecosystems, govern the resilience of system functions to elevated CO2...
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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.
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The objective of Terrestrial-Aquatic Interface (TAI) research in PREMIS is to understand the factors governing C and nutrient movement and transformation through the TAI, and their sensitivities to inundation and salinity within coastal watersheds.
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Accurate characterization of the global downward shortwave (SW) and photosynthetically active radiation (PAR) is fundamental for Earth system modeling and global change research. Combined with a machine-learning method, we used the Earth Polychromatic Imaging Camera (EPIC) data onboard the Deep...
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Last updated on 2023-02-23T19:37:46+00:00 by LN Anderson PerCon SFA Project Publication Experimental Data Catalog The Persistence Control of Engineered Functions in Complex Soil Microbiomes Project (PerCon SFA) at Pacific Northwest National Laboratory ( PNNL ) is a Genomic Sciences Program...

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The Environmental Determinants of Diabetes in the Young (TEDDY) study is searching for factors influencing the development of type 1 diabetes (T1D) in children. Research has shown that there are certain genes that correlate to higher risk of developing T1D, but not all children with these genes...

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