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A FAIR road to a bioAFM databank

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TL;DR - This Nature Methods Comment describes early efforts to build bioAFM-DB, a high-quality databank for biological atomic force microscopy data. Applying FAIR data principles could improve data reuse, comparison, and computational analysis across bioAFM research.

  • The proposed resource focuses on organizing and preserving biological AFM datasets.
  • The authors assess the initiative’s current state and identify challenges in establishing the databank.
  • The Comment outlines potential courses of action rather than reporting experimental results.
  • Details on specific standards, infrastructure, or benchmark results are not provided in the excerpt.

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A FAIR road to a bioAFM databank

Nature Methods Jean-Luc Pellequer, Sebastian Aguayo, Andrea Alessandrini, David Alsteens, Toshio Ando, Audrey Beaussart, Michael Betton, Timo Betz, Kerstin G. Blank, Simone Bovio, Clément Campillo, Claudio Canale, Alexander X. Cartagena-Rivera, Filomena A. Carvalho, Ignacio Casuso, Guillaume Charras, Marti Checa, Liam Collins, Adai Colom, Luca Costa, Etienne Dague, Tanya E. S. Dahms, Pedro Jose de Pablo, Alexandra Delvallée, Simone Dinarelli, Lorna Dougan, Yves F. Dufrêne, Andra C. Dumitru, Yuri M. Efremov, Sofiane El-Kirat-Chatel, Paolo Facci, Georg E. Fantner, Amir Farokh Payam, Cécile Feuillie, Cristina Flors, Nancy Forde, Cécile Formosa-Dague, Gregory Francius, Clemens M. Franz, Kristian Franze, Ricardo Garcia, Sergi Garcia-Manyes, Núria Gavara, Marina I. Giannotti, Marco Girasole, Martin Guthold, George R. Heath, Céline Heu, Peter Hinterdorfer, Jamie K. Hobbs, Bart W. Hoogenboom, Sébastien Janel, Miklós Kellermayer, Petr Klapetek, Noriyuki Kodera, Melanie Koehler, Frank Lafont, Guillaume Lamour, Jessem Landoulsi, Valérie M. Laurent, Philippe Leclère, Malgorzata Lekka, Hongbin Li, Giovanni Longo, Arin Marchesi, Marion Mathelié-Guinlet, Gerald A. Meininger, Ioanna Mela, Pierre-Emmanuel Milhiet, Ruben Millan-Solsona, Tea Mišić Radić, Michaël Molinari, Fernando Moreno-Herrero, Michael A. Nash, Olivier Noël, Yoo Jin Oh, Laia Pasquina-Lemonche, Shivprasad Patil, Patricia Pedraz, Ana Paula Pêgo, Thomas T. Perkins, Martin Pesl, Tri Thanh Pham, Laura Picas, Alessandro Podestà, Johannes Preiner, Jan Přibyl, Roger Proksch, Pierre-Henri Puech, Alice L. B. Pyne, Manfred Radmacher, Lorena Redondo-Morata, Felix Rico, Wouter H. Roos, Robert Ros, Nuno C. Santos, Ugis Sarkans, Tilman E. Schäffer, Hermann Schillers, Zhifeng Shao, Delphine Sicard, Adam Cohen Simonsen, Igor Sokolov, Susana R. Sousa, Bjørn T. Stokke, Andreas Stylianou, Marek Szymonski, Florence Tama, Neil H. Thomson, Takayuki Uchihashi, Massimo Vassalli, Claude Verdier, Anthony Vial, Véronique Vié, Tomaso Zambelli, Renato Zenobi, Peng Zheng, Claire Valotteau 2026-08-28 doi:10.1038/s41592-026-03214-7
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Providers: Hugging Face · N/A OpenAlex · Citations 0 Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-25 14:26:41.360489 UTC

TL;DR - This Nature Methods Comment describes early efforts to build bioAFM-DB, a high-quality databank for biological atomic force microscopy data. Applying FAIR data principles could improve data reuse, comparison, and computational analysis across bioAFM research.

  • The proposed resource focuses on organizing and preserving biological AFM datasets.
  • The authors assess the initiative’s current state and identify challenges in establishing the databank.
  • The Comment outlines potential courses of action rather than reporting experimental results.
  • Details on specific standards, infrastructure, or benchmark results are not provided in the excerpt.
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