Recent studies have shown that reducing the precision of floating‐point calculations in an atmospheric model can improve the model's computational performance without affecting model fidelity, but code changes are needed to accommodate lower precision or to prevent undue round‐off error. For complex...
Filter results
Category
- (-) Computational Research (11)
- (-) Computing & Analytics (5)
- (-) Chemistry (2)
- (-) Atmospheric Science (1)
- Scientific Discovery (72)
- Biology (49)
- Earth System Science (28)
- Human Health (25)
- Microbiome Science (10)
- Integrative Omics (8)
- National Security (7)
- Data Analytics & Machine Learning (5)
- Materials Science (5)
- Energy Resiliency (3)
- Chemical & Biological Signatures Science (2)
- Computational Mathematics & Statistics (2)
- Renewable Energy (2)
- Weapons of Mass Effect (2)
- Coastal Science (1)
- Data Analytics & Machine Learning (1)
- Energy Efficiency (1)
- Energy Storage (1)
- Plant Science (1)
- Solar Energy (1)
Project Type
Publication Type
Tags
- Autoimmunity (4)
- Biomarkers (4)
- Molecular Profiling (4)
- Synthetic (4)
- Type 1 Diabetes (4)
- Machine Learning (3)
- Mass spectrometry-based Omics (3)
- Predictive Modeling (2)
- Alternative Splicing (1)
- DNA Sequence Analysis (1)
- Fish Detection (1)
- Functional Annotation Analysis (1)
- Hydropower (1)
- Kmers (1)
- Marine and Hydrokinetic (1)
- Python (1)
- RNA Sequence Analysis (1)
- Snakemake (1)
- Software Data Analysis (1)
- underwater video (1)
Category
We report the construction of a database of infrared spectra aimed at detecting the gases emitted by biomass burning. The project uses many of the methods of the Pacific Northwest National Laboratory (PNNL) infrared database, but the selection of the species and special experimental considerations...
Category
Category
Christine H Chang, William C Nelson, Abby Jerger, Aaron T Wright, Robert G Egbert, Jason E McDermott, Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding, Bioinformatics Advances , Volume 3, Issue 1, 2023, vbad005, https://doi.org/10.1093/bioadv/vbad005...
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...
Datasets
0
This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities.
Category
Datasets
1
Category
Datasets
1
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...
Category
Datasets
2
This data is a model of synthetic adversarial activity surrounded by noise and was funded by DARPA. The various versions include gradually more complex networks of activities.
Category
Datasets
1
The PNNL-SERDP database was constructed by PNNL to generate the quantitative infrared spectra of gases associated with biomass burning; the reference data are to allow detection and quantification of such gases via infrared absorption spectroscopy. Candidates for the database were selected based on...
Category
Datasets
2
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 .
Category
Datasets
0
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...
Category
Datasets
1
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...
Datasets
3
Category
Datasets
1