ArticleScientific data2023
AtOM, an ontology model to standardize use of brain atlases in tools, workflows, and data infrastructures.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Siibra: a software tool suite for realizing a Multilevel Human Brain Atlas from complex data resources.Nature methods · 2026Article
- Exploring the human brain, from molecules to networks, using siibra.Nature methods · 2026Article
- A Community Standard Multispecies Cell Atlas of the Basal Ganglia.bioRxiv : the preprint server for biology · 2026Article
- A curvilinear coordinate flatmap for visualizing hippocampal structure and development.bioRxiv : the preprint server for biology · 2026Article
- Article
- The Virtual Brain Ontology: A Digital Knowledge Framework for Reproducible Brain Network Modeling.bioRxiv : the preprint server for biology · 2025Article
- Chemoarchitectural studies of the rat hypothalamus and zona incerta.bioRxiv : the preprint server for biology · 2025Article
- Comparison of basal ganglia regions across murine brain atlases using metadata models and the Waxholm Space.Scientific data · 2024Article
- A detailed spatio-temporal atlas of the white matter tracts for the fetal brain.bioRxiv : the preprint server for biology · 2024Article
- Review
- Waxholm Space atlas of the rat brain: a 3D atlas supporting data analysis and integration.Nature methods · 2023Article
- The past, present and future of neuroscience data sharing: a perspective on the state of practices and infrastructure for FAIR.Frontiers in neuroinformatics · 2023Review
- A neuroscientist's guide to using murine brain atlases for efficient analysis and transparent reporting.Frontiers in neuroinformatics · 2023Article
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Authors and funding
7 authors.
Funding
Abstract
Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.