Due to a production error, there was an error in the Affiliations. Instead of “Department of Cardiology, Shanghai Jiao Tong University School of Medicine, Shanghai, China”, it should be “Department of Cardiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China”.
The publisher apologizes for this mistake. The original version of this article has been updated.
Summary
Keywords
heart failure, biomarker, joint nonnegative matrix factorization, diagnostic model, machine learning
Citation
Frontiers Production Office (2022) Erratum: Integration of RNA molecules data with prior-knowledge driven Joint Deep Semi-Negative Matrix Factorization for heart failure study. Front. Genet. 13:1095803. doi: 10.3389/fgene.2022.1095803
Received
11 November 2022
Accepted
11 November 2022
Published
22 November 2022
Approved by
Frontiers Editorial Office, Frontiers Media SA, Switzerland
Volume
13 - 2022
Updates
Copyright
© 2022 Frontiers Production Office.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Frontiers Production Office, production.office@frontiersin.org
This article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.