Predicting drug response of tumors from integrated genomic profiles by deep neural networks-Reference-Cited by-同舟云学术

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Predicting drug response of tumors from integrated genomic profiles by deep neural networks

Published:2019-01 Issue:S1 Volume:12 Page:
ISSN:1755-8794
Container-title:BMC Medical Genomics
language:en
Short-container-title:BMC Med Genomics

Author:

Chiu Yu-Chiao,Chen Hung-I Harry,Zhang Tinghe,Zhang Songyao,Gorthi Aparna,Wang Li-Ju,Huang Yufei,Chen Yidong

Publisher

Springer Science and Business Media LLC

Subject

Genetics (clinical),Genetics

Link

http://link.springer.com/content/pdf/10.1186/s12920-018-0460-9.pdf

Reference41 articles.

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2. Schmitt MW, Loeb LA, Salk JJ. The influence of subclonal resistance mutations on targeted cancer therapy. Nat Rev Clin Oncol. 2016;13(6):335–47.

3. Phillips KA, Veenstra DL, Oren E, Lee JK, Sadee W. Potential role of pharmacogenomics in reducing adverse drug reactions: a systematic review. JAMA : the journal of the American Medical Association. 2001;286(18):2270–9.

4. Hertz DL, Rae J. Pharmacogenetics of cancer drugs. Annu Rev Med. 2015;66:65–81.

5. Mina M, Raynaud F, Tavernari D, Battistello E, Sungalee S, Saghafinia S, Laessle T, Sanchez-Vega F, Schultz N, Oricchio E, et al. Conditional selection of genomic alterations dictates Cancer evolution and oncogenic dependencies. Cancer Cell. 2017;32(2):155–68 e156.

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