Www.nature.com (16)#
A call for public archives for biological image data#
Jan Ellenberg, Jason R. Swedlow, Mary Barlow, Charles E. Cook, Ugis Sarkans, Ardan Patwardhan, Alvis Brazma, Ewan Birney
Tags: Research Data Management
Content type: Publication
Annotated high-throughput microscopy image sets for validation#
Vebjorn Ljosa, Katherine L Sokolnicki, Anne E Carpenter
Broad Bioimage Benchmark Collection (BBBC)
Content type: Collection, Data
Community-developed checklists for publishing images and image analyses#
Christopher Schmied, Michael S Nelson, Sergiy Avilov, Gert-Jan Bakker, Cristina Bertocchi, Johanna Bischof, Ulrike Boehm, Jan Brocher, Mariana T Carvalho, Catalin Chiritescu, Jana Christopher, Beth A Cimini, Eduardo Conde-Sousa, Michael Ebner, Rupert Ecker, Kevin Eliceiri, Julia Fernandez-Rodriguez, Nathalie Gaudreault, Laurent Gelman, David Grunwald, Tingting Gu, Nadia Halidi, Mathias Hammer, Matthew Hartley, Marie Held, Florian Jug, Varun Kapoor, Ayse Aslihan Koksoy, Judith Lacoste, Sylvia Le Dévédec, Sylvie Le Guyader, Penghuan Liu, Gabriel G Martins, Aastha Mathur, Kota Miura, Paula Montero Llopis, Roland Nitschke, Alison North, Adam C Parslow, Alex Payne-Dwyer, Laure Plantard, Rizwan Ali, Britta Schroth-Diez, Lucas Schütz, Ryan T Scott, Arne Seitz, Olaf Selchow, Ved P Sharma, Martin Spitaler, Sathya Srinivasan, Caterina Strambio-De-Castillia, Douglas Taatjes, Christian Tischer, Helena Klara Jambor
Licensed ALL RIGHTS RESERVED
Tags: Bioimage Analysis
Content type: Publication
FAIR High Content Screening in Bioimaging#
Rohola Hosseini, Matthijs Vlasveld, Joost Willemse, Bob van de Water, Sylvia E. Le Dévédec, Katherine J. Wolstencroft
Published 2023-07-17
Licensed CC-BY-4.0
The authors show the utility of Minimum Information for High Content Screening Microscopy Experiments (MIHCSME) for High Content Screening (HCS) data using multiple examples from the Leiden FAIR Cell Observatory, a Euro-Bioimaging flagship node for high content screening and the pilot node for implementing FAIR bioimaging data throughout the Netherlands Bioimaging network.
Tags: FAIR-Principles, Metadata, Research Data Management, Image Data Management, Bioimage Data
Content type: Publication
Image Data Resources#
Content type: Collection, Data, Publication
JIPipe: visual batch processing for ImageJ#
Ruman Gerst, Zoltán Cseresnyés, Marc Thilo Figge
JIPipe is an open-source visual programming language for easy-access pipeline development
Tags: Workflow Engine, Imagej
Content type: Publication, Documentation
MDEmic: a metadata annotation tool to facilitate management of FAIR image data in the bioimaging community#
Susanne Kunis, Sebastian Hänsch, Christian Schmidt, Frances Wong, Caterina Strambio-De-Castillia, Stefanie Weidtkamp-Peters
Licensed ALL RIGHTS RESERVED
Tags: Research Data Management, Metadata
Content type: Publication
MethodsJ2: a software tool to capture metadata and generate comprehensive microscopy methods text#
Joel Ryan, Thomas Pengo, Alex Rigano, Paula Montero Llopis, Michelle S. Itano, Lisa A. Cameron, Guillermo Marqués, Caterina Strambio-De-Castillia, Mark A. Sanders, Claire M. Brown
Tags: Metadata
Content type: Publication
Modeling community standards for metadata as templates makes data FAIR#
Mark A Musen, Martin J O’Connor, Erik Schultes, Marcos Martínez-Romero, Josef Hardi, John Graybeal
Published 2022-11-12
Licensed CC-BY-4.0
The authors have developed a model for scientific metadata, and they have made that model usable by both CEDAR and FAIRware. The approach shows that a formal metadata model can standardize reporting guidelines and that it can enable separate software systems to assist (1) in the authoring of standards-adherent metadata and (2) in the evaluation of existing metadata.
Tags: Data Stewardship, FAIR-Principles, Metadata
Content type: Publication
Multimodal large language models for bioimage analysis#
Shanghang Zhang, Gaole Dai, Tiejun Huang, Jianxu Chen
Licensed [‘CC-BY-NC-SA’]
Multimodal large language models have been recognized as a historical milestone in the field of artificial intelligence and have demonstrated revolutionary potentials not only in commercial applications, but also for many scientific fields. Here we give a brief overview of multimodal large language models through the lens of bioimage analysis and discuss how we could build these models as a community to facilitate biology research
Tags: Bioimage Analysis, Large Language Models, FAIR-Principles, Workflow
Content type: Publication
OME-NGFF: a next-generation file format for expanding bioimaging data-access strategies#
Josh Moore, Chris Allan, Sébastien Besson, Jean-Marie Burel, Erin Diel, David Gault, Kevin Kozlowski, Dominik Lindner, Melissa Linkert, Trevor Manz, Will Moore, Constantin Pape, Christian Tischer, Jason R. Swedlow
Licensed CC-BY-4.0
Tags: Nfdi4Bioimage, Research Data Management
Content type: Publication
REMBI - Recommended Metadata for Biological Images—enabling reuse of microscopy data in biology#
Ugis Sarkans, Wah Chiu, Lucy Collinson, Michele C. Darrow, Jan Ellenberg, David Grunwald, et al.
Published 2021-05-21
Licensed UNKNOWN
Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. The authors propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy.
Tags: Metadata, Bioimage Data, Image Data Management, Research Data Management
Content type: Publication
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8606015/
Reporting and reproducibility in microscopy#
Published 2021-12-03
Licensed UNKNOWN
This Focus issue features a series of papers offering guidelines and tools for improving the tracking and reporting of microscopy metadata with an emphasis on reproducibility and data re-use.
Tags: Reproducibility, Metadata, Bioimage Data
Content type: Collection
The FAIR Guiding Principles for scientific data management and stewardship#
Mark D. Wilkinson, Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, Myles Axton, et. al
Published 2016-03-15
Licensed CC-BY-4.0
This Comment is the first formal publication of the FAIR Principles, and includes the rationale behind them, and some exemplar implementations in the community.
Tags: FAIR-Principles, Research Data Management
Content type: Publication
The FAIR guiding principles for data stewardship - fair enough?#
Martin Boeckhout, Gerhard A. Zielhuis, Annelien L. Bredenoord
Published 2018-05-17
Licensed CC-BY-4.0
The FAIR guiding principles for research data stewardship (findability, accessibility, interoperability, and reusability) look set to become a cornerstone of research in the life sciences. A critical appraisal of these principles in light of ongoing discussions and developments about data sharing is in order.
Tags: FAIR-Principles, Data Stewardship, Sharing
Content type: Publication
ZeroCostDL4Mic: exploiting Google Colab to develop a free and open-source toolbox for Deep-Learning in microscopy#
Lucas von Chamier, Romain F. Laine, Johanna Jukkala, Christoph Spahn, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-pérez, Pieta Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L Jones, Loic Alain Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, Mike Heilemann, Guillaume Jacquemet, Ricardo Henriques
Licensed MIT
Content type: Notebook, Collection
https://www.nature.com/articles/s41467-021-22518-0
https://doi.org/10.1038/s41467-021-22518-0