FAIR Cell Biology Data: From Image Archives to Interoperable Signalling Datasets

This Research Topic is part of our FAIR series. For other Research Topics in the series, please see below:FAIR Metabolomics: Open Datasets, Shared Standards, and the Road to AI-Ready DataFAIR RNA Data: Open Resources for Transcriptomics, Structure, and Regulatory Network ResearchFAIR Genomics: Standards, Repositories, and Reproducibility in Chromatin and Genome ResearchFAIR Mitochondrial Data: Open Resources for Integrative Research in Bioenergetics and DiseaseFAIR Structural Data in the Age of AI: From Deposition to DiscoveryMaking Glycan Data FAIR: Addressing the Interoperability Gap in GlycoscienceCellular biochemistry generates some of the most visually rich and experimentally diverse data in the life sciences, spanning high-content imaging and fluorescence microscopy to proteomics, signalling assays, and single-cell profiling. Despite the growth of dedicated repositories such as the Image Data Resource (IDR) and the BioImage Archive, large volumes of cell biology data remain siloed in local formats, described inconsistently, and inaccessible for reuse.This Research Topic focuses on advancing FAIR data practices across the full spectrum of cellular biochemistry, including metadata standards for cell imaging and high-content screens, interoperability between single-cell atlases and bulk biochemical datasets, and workflows for depositing functional assay data in open repositories. Community image formats such as OME-NGFF represent important progress, but gaps in provenance tracking, instrument metadata, and cross-repository linking remain. The rise of spatial transcriptomics and spatially resolved proteomics creates additional challenges, as spatial context is integral to biological interpretation yet rarely captured in existing metadata schemas.We particularly encourage contributions addressing cell line provenance, FAIR-compliant sharing of flow cytometry and multiplexed imaging data, and interoperability between atlas resources such as the Human Cell Atlas and individual laboratory datasets. Studies demonstrating novel insights enabled by the reuse of open cell biology datasets, and FAIR² Data Articles presenting richly annotated imaging or multimodal datasets with interactive exploration tools, are especially welcome. KEY THEMES• Metadata standards for fluorescence microscopy, high-content imaging, and live-cell data• Community image formats: OME-NGFF, OME-TIFF, and FAIR-compliant image archives• Cell line provenance and authentication data linked to published datasets• Interoperability between single-cell atlases (Human Cell Atlas) and bulk datasets• FAIR data practices for flow cytometry and multiplexed protein imaging• Cross-repository linking of imaging and omics data from the same biological system• Open workflows for depositing functional assay and signalling pathway data• Reuse of open cell biology datasets for cross-species or cross-laboratory comparisons Topic editors: Manuel Aureliano Source: https://www.frontiersin.org/research-topics/83431/fair-cell-biology-data-from-image-archives-to-interoperable-signalling-datasets