Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning-Reference-Cited by-同舟云学术

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Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning

Published:2015-08-22 Issue:1 Volume:10 Page:85-100
ISSN:1574-7891
Container-title:Molecular Oncology
language:en
Short-container-title:

Author:

Dorman Stephanie N.,Baranova Katherina,Knoll Joan H.M.,Urquhart Brad L.,Mariani Gabriella,Carcangiu Maria Luisa,Rogan Peter K.

Publisher

Wiley

Subject

Cancer Research,Genetics,Molecular Medicine,General Medicine,Oncology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1016/j.molonc.2015.07.006/fullpdf

Reference94 articles.

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3. Reliable gene expression measurements from degraded RNA by quantitative real-time PCR depend on short amplicons and a proper normalization;Antonov;Lab. Investig. J. Tech. Methods Pathol,2005

4. Ribonucleotide reductase and cancer: biological mechanisms and targeted therapies;Aye;Oncogene,2014

5. Microtubule-associated proteins as targets in cancer chemotherapy;Bhat;Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res,2007

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