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. 2022 Mar 10;20(3):793–809. doi: 10.1007/s12021-022-09566-7

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Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 4 — Process used to translate local terminology into ontology-based representations and machine-generated names. Using neurondm, phenotypes are first mapped by a user into ontology identifiers (top panel). Neuron types are constructed and neurondm automatically translates these mappings into OWL equivalence statements (middle panel). From the same internal representation of these restrictions neurondm generates a set of human readable labels (bottom panel)