<p>Locating CNV candidates in WGS data using wavelet-compressed Bayesian HMM</p>

John Wiedenhoeft; Alex Cagan; Rimma Kozhemjakina; Rimma Gulevich; Alexander Schliep

doi:10.7490/f1000research.1114670.1

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Wiedenhoeft J, Cagan A, Kozhemjakina R et al. Locating CNV candidates in WGS data using wavelet-compressed Bayesian HMM [version 1; not peer reviewed]. F1000Research 2017, 6(ISCB Comm J):1418 (poster) (https://doi.org/10.7490/f1000research.1114670.1)

NOTE: it is important to ensure the information in square brackets after the title is included in this citation.

Locating CNV candidates in WGS data using wavelet-compressed Bayesian HMM

John Wiedenhoeft¹, Alex Cagan, Rimma Kozhemjakina, Rimma Gulevich, Alexander Schliep

Published 10 Aug 2017 (https://doi.org/10.7490/f1000research.1114670.1)

Author Affiliations

¹ Chalmers University of Technology, Sweden

Copyright © 2017 Wiedenhoeft J 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 10 Aug 2017

Locating CNV candidates in WGS data using wavelet-compressed Bayesian HMM
[version 1; not peer reviewed]

John Wiedenhoeft¹, Alex Cagan, Rimma Kozhemjakina, Rimma Gulevich, Alexander Schliep

Author Affiliations

¹ Chalmers University of Technology, Sweden

Presented at

Joint 25th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and 16th European Conference on Computational Biology (ECCB) 2017

Abstract

Competing Interests

No competing interests were disclosed

Keywords

CNV, WGS, HMM, bayesian inference

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