Abstract
The application of random effect models to different radiation biomarkers, including cytogenetic, protein-based, and gene-expression based biomarkers, is discussed. Explicit case studies are provided for the latter two scenarios, in which random effect models appear especially attractive as they can cope well with the large inter-individual variation which is typical for these biomarkers.
Original language | English |
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Title of host publication | Trends in Mathematics |
Publisher | Springer International Publishing |
Pages | 89-94 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 2017 |
Publication series
Name | Trends in Mathematics |
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Volume | 7 |
ISSN (Print) | 2297-0215 |
ISSN (Electronic) | 2297-024X |
Bibliographical note
Publisher Copyright:© 2017, Springer International Publishing AG.