NIAID Systems Biology for Infectious Diseases Research Program Dataset Catalog

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Principal Investigator

Description

NIAID Omics-Lethal Human Virus Systems Biology Collection

The Omics-LHV Systems Virology project was one of four projects, funded by the NIAID Systems Biology for Infectious Diseases Research Systems Biology Program (funded from 2008-2013), was established in developing and validating predictive models of infectious disease initiation, progression, and anticipated outcomes. Research models derived from experimental study datasets provide a systems-wide host/pathogen molecular interaction networks during infection, using integrated datasets generated from a combination of "omics" technologies, and serve to support a deeper understanding of viral infection complexity and the biological, biochemical, and biophysical molecular processes within microbial organisms as well as their interaction with the host.

Processed Omics Data (available at downloads):

Dataset downloads contain one or more statistically processed data files related to a transcriptomic, proteomic, metabolomic, and/or lipidomic dataset collection associated with a Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) experimental study.

  1. Experiment SM001: 10.25584/LHVSM001/1661974
  2. Experiment SM003: 10.25584/LHVSM003/1661975
  3. Experiment SM012: 10.25584/LHVSM012/1661983
  4. Experiment SCL005: 10.25584/LHVSCL005/1661964
  5. Experiment SCL006: 10.25584/LHVSCL006/1661965
  6. Experiment SCL008: 10.25584/LHVSCL008/1661966
  7. Experiment SCL009: 10.25584/LHVSCL009/1661967
  8. Experiment SCL012: 10.25584/LHVSCL012/1661970
  9. Experiment SHAE002: 10.25584/LHVSHAE002/1661971
  10. Experiment SHAE003: 10.25584/LHVSHAE003/1661972
  11. Experiment SHAE004: 10.25584/LHVSHAE004/1661973

Catalog Citations:

  1. Anderson LN, McDermott J, Waters K, Sims A, Baric R. (2021). Omics Lethal Human Viruses Project, Modeling Host Responses to Severe Acute Respiratory Syndrome (SARS) Infection Post-Processed Data Package DOIs. PNNL DataHub. https://data.pnnl.gov/group/nodes/project/13308. DOI: https://doi.org/10.25584/LHVSARS/1813912
  2. Kelly G. Stratton, & Lisa M. Bramer. (2018). pmartR: Quality Control and Statistics for Mass Spectrometry-Based Biological Data (0.10.0). Zenodo. https://doi.org/10.5281/zenodo.6108668 

Research Highlights

"Virologist’s Coronavirus Paper in Top 50" - Sims’s research among most-downloaded articles on SARS-CoV-2

 

Relevant FAIRsharing Data Standards:

Primary Data Archive Selections

HUPO Proteomics Standard Initiative for Mass Spectrometry

Minimum Information for Biological and Biomedical Investigations

Processed Data Domain-Specific Archive Selections

 

Linked Open Data (Unprocessed Raw Data):

Primary Experimental Host Factor & Study Design Metadata

Primary structured experimental methods, protocols, and metadata supporting derived quantification raw data collections, including fold change values and p-values (.xls,.txt), are available at the Virus Pathogen Resource (ViPR) repository.

Primary Transcriptome Quantification Data (unprocessed expression profiling data by array)

Primary transcriptome experimental data files (mRNA, miRNA) and associated metadata Agilent and Affymetrix microarray experiments are available at the NCBI Gene Expression Omnibus (GEO) under the BioProject collection.

Primary Proteome, Metabolome, Lipidome Quantification Data (unprocessed expression profiling data by mass spectrometry)

Primary omics mass spectrometry quantification data files and associated parameter files (.raw and .mzXML) including those used for accurate mass and time (AMT) tag database generation have been uploaded to the PeptideAtlasPRIDE, and MassIVE data repositories. Proteomics data used to populate accurate mass and time (AMT) tag databases is stored at both PRIDE and PeptideAtlas, and quantitative proteomics data generated using the AMT tag approach is stored only at PeptideAtlas. 

 

Acknowledgements

The datasets described here was funded in whole or in part by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services under Contract No. HHSN272200800060C. Omics data generated by the Systems Virology Proteomics, Metabolomics, and Lipidomics Core were performed at Pacific Northwest National Laboratory (PNNL) in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the Department of Energy’s (DOE) Office of Biological and Environmental Research located in Richland, WA. PNNL is operated by the Battelle Memorial Institute for the DOE under contract number DE-AC05-76RLO1830. 

Project status

Active
Datasets (11)
English
Publications (4)
People (3)

Tom Metz is a Principal Investigator within the Integrative Omics group at PNNL and the Metabolomics Team Lead for a group of scientists that focuses on development and applications of high throughput metabolomics and lipidomics methods to various biological questions. He has worked to develop state...

Dr. Jason McDermott, senior research scientist, has extensive research experience in molecular and structural virology and data resource design, data integration and prediction of biological networks, bridging experimental and computational biology. Currently, his research interests include data...

Lindsey Anderson’s research has been dedicated to the identification and characterization of novel, targeted and non-targeted, functional metabolic interactions using a high-throughput systems biology and computational biology approach. Her expertise in functional metabolism and multidisciplinary...

Data Sources (3)
Institutions (1)