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Authors: Alexander J. Titus 1 ; 2 ; Carly A. Bobak 1 and Brock C. Christensen 2

Affiliations: 1 Dartmouth School of Graduate and Advanced Studies, United States ; 2 Dartmouth Geisel School of Medicine, United States

Keyword(s): Deep Learning, DNA Methylation, Breast Cancer, Epigenetics, Variational Autoencoders, TCGA.

Abstract: In the era of precision medicine and cancer genomics, data are being generated so quickly that it is difficult to fully appreciate the extent of what is discoverable. DNA methylation, a chemical modification to DNA, has been shown to be a significant factor in many cancers and is a candidate data source with ample features for model traing. However, the black-box nature of non-linear models, such as those in deep learning, and a lack of accurately labeled ground truth data have limited the same rapid adoption in this space that other methods have experienced. In this article, we discuss the applications of unsupervised learning through the use of variational autoencoders using DNA methylation data and motivate further work with initial results using breast cancer data provided by The Cancer Genome Atlas. We show that a logistic regression classifier trained on the learned latent methylome accurately classifies disease subtype.

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Paper citation in several formats:
Titus, A.; Bobak, C. and Christensen, B. (2018). A New Dimension of Breast Cancer Epigenetics. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - BIOINFORMATICS; ISBN 978-989-758-280-6; ISSN 2184-4305, SciTePress, pages 140-145. DOI: 10.5220/0006636401400145

@conference{bioinformatics18,
author={Alexander J. Titus. and Carly A. Bobak. and Brock C. Christensen.},
title={A New Dimension of Breast Cancer Epigenetics},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - BIOINFORMATICS},
year={2018},
pages={140-145},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006636401400145},
isbn={978-989-758-280-6},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - BIOINFORMATICS
TI - A New Dimension of Breast Cancer Epigenetics
SN - 978-989-758-280-6
IS - 2184-4305
AU - Titus, A.
AU - Bobak, C.
AU - Christensen, B.
PY - 2018
SP - 140
EP - 145
DO - 10.5220/0006636401400145
PB - SciTePress

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