<p>Estimation of optimal number of independent components for patient classification and prediction of their survival</p>

Maryna Chepeleva; Mikalai M. Yatskou; Petr V. Nazarov

doi:10.7490/f1000research.1117820.1

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Chepeleva M, Yatskou MM and Nazarov PV. Estimation of optimal number of independent components for patient classification and prediction of their survival [version 1; not peer reviewed]. F1000Research 2020, 9:126 (poster) (https://doi.org/10.7490/f1000research.1117820.1)

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Estimation of optimal number of independent components for patient classification and prediction of their survival

Maryna Chepeleva¹, Mikalai M. Yatskou, Petr V. Nazarov

Published 20 Feb 2020 (https://doi.org/10.7490/f1000research.1117820.1)

Author Affiliations

¹ Belarusian State University, Belarus

Copyright © 2020 Chepeleva M 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 20 Feb 2020

Estimation of optimal number of independent components for patient classification and prediction of their survival
[version 1; not peer reviewed]

Maryna Chepeleva¹, Mikalai M. Yatskou, Petr V. Nazarov

Author Affiliations

¹ Belarusian State University, Belarus

Presented at

Applied Bioinformatics in Life Sciences (3rd edition) 2020

Abstract

Competing Interests

No competing interests were disclosed

Keywords

independent component analysis, deconvolution, cancer, diagnostics, survival, transcriptomics

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