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Correction ARTICLE

Front. Genet., 13 September 2019 | https://doi.org/10.3389/fgene.2019.00923

Corrigendum: NCNet: Deep Learning Network Models for Predicting Function of Non-Coding DNA

Hanyu Zhang1,2, Che-Lun Hung3,4,5,6*, Meiyuan Liu7, Xiaoye Hu7 and Yi-Yang Lin6
  • 1College of Computing and Informatics, Providence University, Taichung City, Taiwan
  • 2Labo MICS, École CentraleSup élec, Université Paris Saclay, Gif-sur-Yvette, France
  • 3Department and Graduate Institute of Computer Science and Information Engineering, Chang Gung University, Taoyuan City, Taiwan
  • 4Division of Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital, Taoyuan City, Taiwan
  • 5AI Innovation Research Center, Chang Gung University, Taoyuan City, Taiwan
  • 6Department of Computer Science and Communication Engineering, Providence University, Taichung City, Taiwan
  • 7Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China

A corrigendum on
NCNet: Deep Learning Network Models for Predicting Function of Non-Coding DNA

by Zhang H, Hung C-L, Liu M, Hu X and Lin Y-Y (2019). Front. Genet. 10:432. doi: 10.3389/fgene.2019.00432

In the published article, there was an error in affiliation “1.” The affiliation “Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China” should be moved to affiliation “7” and should be removed for the first and corresponding authors. Additionally, all subsequent affiliations should move up in order.

The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.

Keywords: Non-coding DNA, residual learning, LSTM, sequence to sequence learning, deep learning

Citation: Zhang H, Hung C-L, Liu M, Hu X and Lin Y-Y (2019) Corrigendum: NCNet: Deep Learning Network Models for Predicting Function of Non-Coding DNA. Front. Genet. 10:923. doi: 10.3389/fgene.2019.00923

Received: 03 September 2019; Accepted: 04 September 2019;
Published: 13 September 2019.

Approved by: Frontiers Editorial Office, Frontiers Media SA, Switzerland

Copyright © 2018 Zhang, Hung, Liu, Hu and Lin. 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: Che-Lun Hung, clhung@mail.cgu.edu.tw