Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization

10.1186/s12885-017-3500-5

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Bibliographic Details
Main Authors:	Wang, L, Li, X, Zhang, L, Gao, Q
Other Authors:	MATHEMATICS
Format:	Article
Published:	Springer Nature 2019
Subjects:	Anticancer drug response prediction Drug repositioning Matrix factorization Precision cancer medicines Algorithms Antineoplastic Agents Cell Line, Tumor Computational Biology Databases, Factual Dose-Response Relationship, Drug Drug Repositioning Drug Resistance, Neoplasm Humans Pharmacogenetics Pharmacogenomic Variants Precision Medicine Reproducibility of Results
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/156497
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Institution:	National University of Singapore

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spelling	sg-nus-scholar.10635-1564972024-04-17T03:02:28Z Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization Wang, L Li, X Zhang, L Gao, Q MATHEMATICS Anticancer drug response prediction Drug repositioning Matrix factorization Precision cancer medicines Algorithms Antineoplastic Agents Cell Line, Tumor Computational Biology Databases, Factual Dose-Response Relationship, Drug Drug Repositioning Drug Resistance, Neoplasm Humans Pharmacogenetics Pharmacogenomic Variants Precision Medicine Reproducibility of Results 10.1186/s12885-017-3500-5 BMC Cancer 17 1 513- 2019-07-08T05:59:51Z 2019-07-08T05:59:51Z 2017-08-02 2019-07-08T04:59:41Z Article Wang, L, Li, X, Zhang, L, Gao, Q (2017-08-02). Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization. BMC Cancer 17 (1) : 513-. ScholarBank@NUS Repository. https://doi.org/10.1186/s12885-017-3500-5 1471-2407 https://scholarbank.nus.edu.sg/handle/10635/156497 Springer Nature Elements
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Anticancer drug response prediction Drug repositioning Matrix factorization Precision cancer medicines Algorithms Antineoplastic Agents Cell Line, Tumor Computational Biology Databases, Factual Dose-Response Relationship, Drug Drug Repositioning Drug Resistance, Neoplasm Humans Pharmacogenetics Pharmacogenomic Variants Precision Medicine Reproducibility of Results
spellingShingle	Anticancer drug response prediction Drug repositioning Matrix factorization Precision cancer medicines Algorithms Antineoplastic Agents Cell Line, Tumor Computational Biology Databases, Factual Dose-Response Relationship, Drug Drug Repositioning Drug Resistance, Neoplasm Humans Pharmacogenetics Pharmacogenomic Variants Precision Medicine Reproducibility of Results Wang, L Li, X Zhang, L Gao, Q Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization
description	10.1186/s12885-017-3500-5
author2	MATHEMATICS
author_facet	MATHEMATICS Wang, L Li, X Zhang, L Gao, Q
format	Article
author	Wang, L Li, X Zhang, L Gao, Q
author_sort	Wang, L
title	Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization
title_short	Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization
title_full	Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization
title_fullStr	Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization
title_full_unstemmed	Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization
title_sort	improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization
publisher	Springer Nature
publishDate	2019
url	https://scholarbank.nus.edu.sg/handle/10635/156497
_version_	1800913652441677824

Improved anticancer drug response prediction in cell lines using matrix factorization with similarity regularization

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