Miki Ikebe1,2‡
Kota Aoki
Mitsuko Hayashi-Nishino
Kunihiko Nishino
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- 1SANKEN (Institute of Scientific and Industrial Research), Osaka University, Osaka, Japan
- 2Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Japan
- 3Artificial Intelligence Research Center (AIRC-SANKEN), Osaka University, Osaka, Japan
- 4Center for Biosystems Dynamics Research, RIKEN, Suita, Japan
- 5Universal Biology Institute, The University of Tokyo, Tokyo, Japan
- 6Center for Infectious Disease Education and Research, Osaka University, Osaka, Japan
A Corrigendum on
Bioinformatic analysis reveals the association between bacterial morphology and antibiotic resistance using light microscopy with deep learning
by Ikebe, M., Aoki, K., Hayashi-Nishino, M., Furusawa, C., and Nishino, K. (2024). Front. Microbiol. 15:1450804. doi: 10.3389/fmicb.2024.1450804
In the published article, there was an error in the Data availability statement. It was incorrectly stated that the names of the repository (and accession number) can be found in the article or Supplementary material. The correct Data Availability statement appears below.
Data availability statement
The datasets presented in this study can be found in the online repository; https://doi.org/10.6084/m9.figshare.c.7757147.v1.
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.
Publisher's note
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.
Keywords: antibiotic resistance, light microscopy, bacterial morphology, deep learning, bioinformatic analysis
Citation: Ikebe M, Aoki K, Hayashi-Nishino M, Furusawa C and Nishino K (2025) Corrigendum: Bioinformatic analysis reveals the association between bacterial morphology and antibiotic resistance using light microscopy with deep learning. Front. Microbiol. 16:1607769. doi: 10.3389/fmicb.2025.1607769
Received: 08 April 2025; Accepted: 09 April 2025;
Published: 17 April 2025.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2025 Ikebe, Aoki, Hayashi-Nishino, Furusawa and Nishino. 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: Kota Aoki, YW9raS5rQHRvdHRvcmktdS5hYy5qcA==; Mitsuko Hayashi-Nishino, bW5pc2hpbm9Ac2Fua2VuLm9zYWthLXUuYWMuanA=; Kunihiko Nishino, bmlzaGlub0BzYW5rZW4ub3Nha2EtdS5hYy5qcA==
†Present address: Kota Aoki Department of Electrical Engineering and Computer Science, Faculty of Engineering, Tottori University, Tottori, Japan
‡These authors have contributed equally to this work