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Title: Prediction of Drug Response in Cancerous Cell Lines Using Machine Learning Algorithms

Abstract

No abstract provided.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (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. doi:10.2172/1396149.
Washburn, Ammon Joseph, Sherman, Thomas James, Anghel, Marian, Garcia Cardona, Cristina, and Gans, Jason David. Fri . "Prediction of Drug Response in Cancerous Cell Lines Using Machine Learning Algorithms". United States. doi: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},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Sep 29 00:00:00 EDT 2017},
month = {Fri Sep 29 00:00:00 EDT 2017}
}

Technical Report:

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