NIHMS1933008-supplement-Supplementary_data_1 (1)
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NIHMS1933008-supplement-Supplementary_data_1 (1).docx
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Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[ "020:00" ] |
| contactPoint |
{ "fn": "Holly Mortensen", "hasEmail": "mailto:mortensen.holly@epa.gov" } |
| description | This ScienceHub entry provides Associated Data (Supplementary data 1) from the published manuscript Comput Toxicol. 2023 Jan 25;25:100261. doi: 10.1016/j.comtox.2023.100261. Further availability of data, as stated in the manuscript, will be made available on request. This dataset is associated with the following publication: Romano, J., L. Mei, J. Senn, J. Moore, and H. Mortensen. Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data science. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 25: 100261, (2023). |
| distribution |
[ { "title": "NIHMS1933008-supplement-Supplementary_data_1 (1).docx", "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document", "downloadURL": "https://pasteur.epa.gov/uploads/10.23719/1532078/NIHMS1933008-supplement-Supplementary_data_1%20%281%29.docx" } ] |
| identifier | https://doi.org/10.23719/1532078 |
| keyword |
[ "Graph data science", "adverse outcome pathway", "genetic programming", "liver cancer" ] |
| license | https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html |
| modified | 2023-01-25 |
| 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/10.1016/j.comtox.2023.100261", "https://pmc.ncbi.nlm.nih.gov/articles/instance/10569310/bin/NIHMS1933008-supplement-Supplementary_data_1.docx", "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10569310" ] |
| rights |
null
|
| title | NIHMS1933008-supplement-Supplementary_data_1 (1) |