Prediction of Drug Response in Cancerous Cell Lines Using Machine Learning Algorithms
Abstract
No abstract provided.
- Authors:
-
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1396149
- Report Number(s):
- LA-UR-17-28891
- DOE Contract Number:
- AC52-06NA25396
- Resource Type:
- Technical Report
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; 97 MATHEMATICS AND COMPUTING; Computer Science; Mathematics; Machine learning, feature selection, multilayer perceptron, elastic net
Citation Formats
Washburn, Ammon Joseph, Sherman, Thomas James, Anghel, Marian, Garcia Cardona, Cristina, and Gans, Jason David. Prediction of Drug Response in Cancerous Cell Lines Using Machine Learning Algorithms. United States: N. p., 2017.
Web. doi:10.2172/1396149.
Washburn, Ammon Joseph, Sherman, Thomas James, Anghel, Marian, Garcia Cardona, Cristina, & Gans, Jason David. Prediction of Drug Response in Cancerous Cell Lines Using Machine Learning Algorithms. United States. https://doi.org/10.2172/1396149
Washburn, Ammon Joseph, Sherman, Thomas James, Anghel, Marian, Garcia Cardona, Cristina, and Gans, Jason David. 2017.
"Prediction of Drug Response in Cancerous Cell Lines Using Machine Learning Algorithms". United States. https://doi.org/10.2172/1396149. https://www.osti.gov/servlets/purl/1396149.
@article{osti_1396149,
title = {Prediction of Drug Response in Cancerous Cell Lines Using Machine Learning Algorithms},
author = {Washburn, Ammon Joseph and Sherman, Thomas James and Anghel, Marian and Garcia Cardona, Cristina and Gans, Jason David},
abstractNote = {No abstract provided.},
doi = {10.2172/1396149},
url = {https://www.osti.gov/biblio/1396149},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Sep 29 00:00:00 EDT 2017},
month = {Fri Sep 29 00:00:00 EDT 2017}
}
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