<p>Efficient nonlinear genotype-to-phenotype prediction for heel bone mineral density</p>

Aleksandr Medvedev; Elena Nabieva; Satyarth Mishra Sharma; Dmitry Yarotsky

doi:10.7490/f1000research.1118188.1

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Medvedev A, Nabieva E, Mishra Sharma S and Yarotsky D. Efficient nonlinear genotype-to-phenotype prediction for heel bone mineral density [version 1; not peer reviewed]. F1000Research 2020, 9(ISCB Comm J):908 (poster) (https://doi.org/10.7490/f1000research.1118188.1)

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Efficient nonlinear genotype-to-phenotype prediction for heel bone mineral density

Aleksandr Medvedev¹, Elena Nabieva, Satyarth Mishra Sharma, Dmitry Yarotsky

Published 04 Aug 2020 (https://doi.org/10.7490/f1000research.1118188.1)

Author Affiliations

¹ Skolkovo Institute of Science and Technology, Russian Federation

Copyright © 2020 Medvedev A et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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CITE

Published 04 Aug 2020

Efficient nonlinear genotype-to-phenotype prediction for heel bone mineral density
[version 1; not peer reviewed]

Aleksandr Medvedev¹, Elena Nabieva, Satyarth Mishra Sharma, Dmitry Yarotsky

Author Affiliations

¹ Skolkovo Institute of Science and Technology, Russian Federation

Presented at

28th International Conference on Intelligent Systems for Molecular Biology (ISMB) 2020

Abstract

Competing Interests

No competing interests were disclosed

Keywords

XGBoost, phenotype prediction, lasso, genotype data, uk biobank, neural networks, bone mineral density, osteoporosis

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