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Machine learning techniques combined with dose profiles indicate radiation response biomarkers Cover

Machine learning techniques combined with dose profiles indicate radiation response biomarkers

International Journal of Applied Mathematics and Computer Science
Volume 29 (2019): Issue 1 (March 2019)
By: Anna Papiez,  Christophe Badie and  Joanna Polanska  
Open Access
|Mar 2019

Authors

Anna Papiez

Data Mining Group, Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland

Christophe Badie

Cancer Mechanisms and Biomarkers, Radiation Effects Department, Centre for Radiation, Chemical & Environmental Hazards, Public Health England

Joanna Polanska

joanna.polanska@polsl.pl

Data Mining Group, Institute of Automatic Control, Silesian University of Technology, Gliwice, Poland
DOI: https://doi.org/10.2478/amcs-2019-0013 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
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Language: English
Page range: 169 - 178
Submitted on: Feb 28, 2018
Accepted on: Oct 18, 2018
Published on: Mar 29, 2019
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
machine learning,
gene profiling,
radiation response,
multiple random validation,
transcription
Related subjects:
Mathematics,
Applied mathematics

© 2019 Anna Papiez, Christophe Badie, Joanna Polanska, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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