{"accessLevel": "public", "bureauCode": ["020:00"], "contactPoint": {"fn": "Yong Ho Kim", "hasEmail": "mailto:kim.yongho@epa.gov"}, "description": "This dataset was generated to support the differential expression analysis, transcriptomic similarity scoring analysis, exposure chemistry profiles, mouse pulmonary toxicity measures and associated figures contained within the manuscript. \n\nThis dataset is associated with the following publication:\nKoval, L., C. Carberry, Y.H. Kim, E. McDermott, H. Hartwell, I. Jaspers, M. Gilmour, and J. Rager. Wildfire Variable Toxicity: Identifying Biomass Smoke Exposure Groupings through Transcriptomic Similarity Scoring.   International Journal of Environmental Science and Technology. Springer, Heidelburg,  GERMANY, 56(23): 17131-17142, (2022).", "distribution": [{"accessURL": "https://github.com/Ragerlab/Script_for_Wildfire-Variable-Toxicity--Identifying-Biomass-Smoke-Exposure-Groupings-through-Transcri", "title": "https://github.com/Ragerlab/Script_for_Wildfire-Variable-Toxicity--Identifying-Biomass-Smoke-Exposure-Groupings-through-Transcri"}, {"accessURL": "https://dataverse.unc.edu/dataverse/ragerlab", "title": "https://dataverse.unc.edu/dataverse/ragerlab"}, {"accessURL": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164542", "title": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE164542"}], "identifier": "https://doi.org/10.23719/1531715", "keyword": ["toxicology", "wildfire", "air pollution", "biofuels", "bioinformatics"], "license": "https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html", "modified": "2022-09-01", "programCode": ["020:000"], "publisher": {"name": "U.S. EPA Office of Research and Development (ORD)", "subOrganizationOf": {"name": "U.S. Environmental Protection Agency", "subOrganizationOf": {"name": "U.S. Government"}}}, "references": ["https://doi.org/10.1021/acs.est.2c06043", "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10777820"], "rights": null, "title": "Wildfire Transcriptomic Similarity Scoring Data"}