Predicting accurate nuclear magnetic resonance chemical shieldings relies upon cancellation of different types of errors between the theoretically calculated shielding constant of the analyte of interest and the reference. Often, the intrinsic error in computed shieldings due to basis sets...
Filter results
Content type
Tags
- (-) Synthetic (14)
- Virology (79)
- Immune Response (53)
- Time Sampled Measurement Datasets (50)
- Gene expression profile data (47)
- Differential Expression Analysis (46)
- Homo sapiens (34)
- Mass spectrometry data (31)
- Multi-Omics (30)
- Viruses (26)
- Omics (25)
- Health (23)
- Virus (23)
- Soil Microbiology (21)
- MERS-CoV (18)
- Mus musculus (18)
- Mass Spectrometry (14)
- sequencing (13)
- West Nile virus (13)
- Genomics (12)
- Ebola (11)
- Influenza A (11)
- PerCon SFA (10)
- High Throughput Sequencing (9)
- Metagenomics (9)
- Resource Metadata (9)
- Microbiome (8)
- Proteomics (8)
- Machine Learning (7)
- Microarray (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
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
7
Category
Datasets
1
This data was generated by the organization IvySys. Activities can be phone calls, transactions, or any other type of communications. Most of the files are of the type .edges, .rdf, or .csv; but all can be opened in a text editor. A good introduction to this data can be found in \Tutorial1\MAA...
Category
This data was generated by the organization GORDIAN. Activities can be phone calls, transactions, or any other type of communications. Most of the files are of the type .csv; and can be opened in a text editor. A description of the data and how to read it can be found in the html files for the...