Exhaled breath condensate proteomics represent a low-cost, non-invasive alternative for examining upper respiratory health. EBC has previously been used for the discovery and validation of detected exhaled volatiles and non-volatile biomarkers of disease related to upper respiratory system distress...
Filter results
Category
- (-) National Security (21)
- (-) Data Analytics & Machine Learning (8)
- (-) Computational Mathematics & Statistics (5)
- (-) High-Performance Computing (1)
- (-) Wind Energy (1)
- Scientific Discovery (307)
- Biology (198)
- Earth System Science (136)
- Human Health (102)
- Integrative Omics (73)
- Microbiome Science (42)
- Computational Research (23)
- Computing & Analytics (14)
- Chemistry (10)
- Energy Resiliency (9)
- Materials Science (7)
- Visual Analytics (6)
- Chemical & Biological Signatures Science (5)
- Weapons of Mass Effect (5)
- Atmospheric Science (4)
- Coastal Science (4)
- Ecosystem Science (4)
- Renewable Energy (4)
- Data Analytics & Machine Learning (3)
- Plant Science (3)
- Cybersecurity (2)
- Distribution (2)
- Electric Grid Modernization (2)
- Energy Efficiency (2)
- Energy Storage (2)
- Grid Cybersecurity (2)
- Solar Energy (2)
- Bioenergy Technologies (1)
- Computational Mathematics & Statistics (1)
- Grid Analytics (1)
- Subsurface Science (1)
- Terrestrial Aquatics (1)
- Transportation (1)
Content type
Tags
- Machine Learning (6)
- Type 1 Diabetes (6)
- Autoimmunity (5)
- Synthetic (5)
- Biomarkers (4)
- Molecular Profiling (4)
- Predictive Modeling (4)
- Mass spectrometry-based Omics (3)
- Alternative Splicing (2)
- Cybersecurity (2)
- Electrical energy (2)
- Proteomics (2)
- Data Analysis (1)
- Data inventory (1)
- Droughts (1)
- EBC (1)
- Exhaled Breath Condensate (1)
- Extreme weather (1)
- Fires (1)
- Heatwaves (1)
- High-Performance Computing (1)
- ML/AI (1)
- Omics (1)
- Output Databases (1)
- Quantification (1)
- TMT (1)
Dr. Gao obtained her Ph.D degree in Chemistry from institute of chemistry, Chinese Academy of Science. His Ph.D research focused on multiscale modeling of morphology and properties of polymeric materials, polymer processing and unveiling the process–properties relationships. (atomic to coarse...
Category
HDF5 file containing 10,000 hydraulic transmissivity inputs and the corresponding hydraulic pressure field outputs for a two-dimensional saturated flow model of the Hanford Site. The inputs are generated by sampling a 1,000-dimensional Kosambi-Karhunen-Loève (KKL) model of the transmissivity field...
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
Fusarium sp. DS682 Proteogenomics Statistical Data Analysis of SFA dataset download: 10.25584/KSOmicsFspDS682/1766303 . GitHub Repository Source: https://github.com/lmbramer/Fusarium-sp.-DS-682-Proteogenomics MaxQuant Export Files (txt) Trelliscope Boxplots (jsonp) Fusarium Report (.Rmd, html)...
Datasets
1
Category
Datasets
1
Category
Datasets
7
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 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...
Datasets
1
The Diabetes Autoimmunity Study in the Young (DAISY) seeks to find environmental factors that can trigger the development of type 1 diabetes (T1D) in children. DAISY follows children with high-risk of developing T1D based on family history or genetic markers. Genes, diets, infections, and...
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
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 &...