Receptor Status Prediction in Breast Cancer Patients Using Machine Learning Pipeline on DNA Methylation Data

Author:

Gupta Saksham1

Affiliation:

1. International Institute of Information Technology, India

Publisher

ACM

Reference23 articles.

1. Yoon S Won HS Kang K Qiu K Park WJ Ko YH. Hormone Receptor-Status Prediction in Breast Cancer Using Gene Expression Profiles and Their Macroscopic Landscape. Cancers (Basel) 2020 May;12(5). Yoon S Won HS Kang K Qiu K Park WJ Ko YH. Hormone Receptor-Status Prediction in Breast Cancer Using Gene Expression Profiles and Their Macroscopic Landscape. Cancers (Basel) 2020 May;12(5).

2. Gown AM. Current issues in ER and HER2 testing by IHC in breast cancer. Modern Pathology 2008 May;21(2): S8 – S15 . https://doi.org/10.1038/modpathol.2008.34. 10.1038/modpathol.2008.34 Gown AM. Current issues in ER and HER2 testing by IHC in breast cancer. Modern Pathology 2008 May;21(2): S8–S15. https://doi.org/10.1038/modpathol.2008.34.

3. Parker JS , Mullins M , Cheang MC , Leung S , Voduc D , Vickery T , Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009 Mar;27(8): 1160 – 1167 . Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009 Mar;27(8):1160–1167.

4. Paquet ER , Hallett MT. Absolute assignment of breast cancer intrinsic molecular subtype. J Natl Cancer Inst 2015 Jan;107(1):357. Paquet ER, Hallett MT. Absolute assignment of breast cancer intrinsic molecular subtype. J Natl Cancer Inst 2015 Jan;107(1):357.

5. Levy JJ Titus AJ Salas LA Christensen BC. PyMethylProcess-convenient high-throughput preprocessing workflow for DNA methylation data. Bioinformatics (Oxford England) 2019 Dec;35(24):5379-5381.https://doi.org/10.1093/bioinformatics/btz594. 10.1093/bioinformatics

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