Meta-analysis of transcriptomic datasets using benchmark dose modeling shows value in supporting radiation risk assessment.
Saved in:
| Title: | Meta-analysis of transcriptomic datasets using benchmark dose modeling shows value in supporting radiation risk assessment. |
|---|---|
| Authors: | Chauhan V; Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada., Adam N; Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada., Kuo B; Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada., Williams A; Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada., Yauk CL; Environmental Health Science and Research Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada., Wilkins R; Consumer and Clinical Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada., Stainforth R; Radiation Protection Bureau, Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Canada. |
| Source: | International journal of radiation biology [Int J Radiat Biol] 2021; Vol. 97 (1), pp. 31-49. Date of Electronic Publication: 2020 Aug 18. |
| Publication Type: | Journal Article; Meta-Analysis |
| Journal Info: | Publisher: Taylor & Francis Country of Publication: England NLM ID: 8809243 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1362-3095 (Electronic) Linking ISSN: 09553002 NLM ISO Abbreviation: Int J Radiat Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1362-3095 |
|---|---|
| DOI: | 10.1080/09553002.2020.1798543 |
