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---
layout: ontology_detail
layout: ontology_detail
id: bmont
title: Biomarker Ontology
browsers:
- title: BioPortal Ontology Browser
label: BioPortal
url: [https://bioportal.bioontology.org/ontologies/BMONT]
contact:
email: [email protected]
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@Astghik-S: Unfortunately this is a blocker. The contact MUST be a person who can be responsive to community requests and is active in the development and maintenance of the ontology. Perhaps you are the right person since you are the ontology submitter and the one authoring the metadata record?

github: akodamullil
label: Alpha Tom Kodamullil
orcid: 0000-0001-9896-3531
description: An application ontology that represents comprehensive knowledge involving a variety of fields of medical and biological aspects.
domain: health
homepage: https://github.com/SCAI-BIO/BiomarkerOntology
in_foundry_order:
license:
label: CC BY 4.0
url: http://creativecommons.org/licenses/by/4.0/
preferredPrefix: BMONT
products:
- id: BMONT.owl
- id: bmont.obo
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I see bmont.obo listed here as a product but there is no corresponding file in the https://github.com/SCAI-BIO/BiomarkerOntology repository. Same applies to BMONT.owl.

Could you please confirm where these files are located?

description: Includes axioms linking to other ontologies, but no imports of those ontologies
publications:
- id:
title:
- id:
title: Using ontologies to describe mouse phenotypes
repository: https://github.com/SCAI-BIO/BiomarkerOntology
tracker: https://github.com/SCAI-BIO/BiomarkerOntology/issue
usages:
- description: BMONT is proposed to be used for improving biomarker identification tasks, as well as a supportive integratable tool for abundant AI techniques, such as Machine Learning (ML) and Large Learning Model (LLM).
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When we describe usage, we do want documented usage. i.e. the use of BMONT and terms from BMONT in associations, publications, data portal, etc. If there are no documented usage then please remove the usages section.

Suggested change
usages:
- description: BMONT is proposed to be used for improving biomarker identification tasks, as well as a supportive integratable tool for abundant AI techniques, such as Machine Learning (ML) and Large Learning Model (LLM).


activity_status: true
---