CORRECTION article

Front. Microbiol., 17 April 2025

Sec. Infectious Agents and Disease

Volume 16 - 2025 | https://doi.org/10.3389/fmicb.2025.1607769

Corrigendum: Bioinformatic analysis reveals the association between bacterial morphology and antibiotic resistance using light microscopy with deep learning

  • 1. SANKEN (Institute of Scientific and Industrial Research), Osaka University, Osaka, Japan

  • 2. Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Japan

  • 3. Artificial Intelligence Research Center (AIRC-SANKEN), Osaka University, Osaka, Japan

  • 4. Center for Biosystems Dynamics Research, RIKEN, Suita, Japan

  • 5. Universal Biology Institute, The University of Tokyo, Tokyo, Japan

  • 6. Center for Infectious Disease Education and Research, Osaka University, Osaka, Japan

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.

Statements

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.

Summary

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, Switzerland

Volume

16 - 2025

Updates

Copyright

*Correspondence: Kota Aoki, Mitsuko Hayashi-Nishino, Kunihiko Nishino,

‡These authors have contributed equally to this work

†Present address: Kota Aoki Department of Electrical Engineering and Computer Science, Faculty of Engineering, Tottori University, Tottori, Japan

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.

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