The Medical Action Ontology: A Tool for Annotating and Analyzing Treatments and Clinical Management of Human Disease

Abstract Navigating the vast landscape of clinical literature to find optimal treatments and management strategies can be a challenging task, especially for rare diseases. To address this task, we introduce the Medical Action Ontology (MAxO), the first ontology specifically designed to organize medical procedures, therapies, and interventions in a structured way. Currently, MAxO contains 1757 medical action terms added through a combination of manual and semi-automated processes. MAxO was developed with logical structures that make it compatible with several other ontologies within the Open Biological and Biomedical Ontologies (OBO) Foundry. These cover a wide range of biomedical domains, from human anatomy and investigations to the chemical and protein entities involved in biological processes.We have created a database of over 16000 annotations that describe diagnostic modalities for specific phenotypic abnormalities as defined by the Human Phenotype Ontology (HPO). Additionally, 413 annotations are provided for medical actions for 189 rare diseases. We have developed a web application called POET (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://poet.jax.org/">https://poet.jax.org/</jats:ext-link>) for the community to use to contribute MAxO annotations.MAxO provides a computational representation of treatments and other actions taken for the clinical management of patients. The development of MAxO is closely coupled to the Mondo Disease Ontology (Mondo) and the Human Phenotype Ontology (HPO) and expands the scope of our computational modeling of diseases and phenotypic features to include diagnostics and therapeutic actions. MAxO is available under the open-source CC-BY 4.0 license (<jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/monarch-initiative/MAxO">https://github.com/monarch-initiative/MAxO</jats:ext-link>)..

Medienart:

Preprint

Erscheinungsjahr:

2024

Erschienen:

2024

Enthalten in:

bioRxiv.org - (2024) vom: 23. Apr. Zur Gesamtaufnahme - year:2024

Sprache:

Englisch

Beteiligte Personen:

Carmody, Leigh C [VerfasserIn]
Gargano, Michael A [VerfasserIn]
Toro, Sabrina [VerfasserIn]
Vasilevsky, Nicole A [VerfasserIn]
Adam, Margaret P [VerfasserIn]
Blau, Hannah [VerfasserIn]
Chan, Lauren E [VerfasserIn]
Gomez-Andres, David [VerfasserIn]
Horvath, Rita [VerfasserIn]
Kraus, Megan L [VerfasserIn]
Ladewig, Markus S [VerfasserIn]
Lewis-Smith, David [VerfasserIn]
Lochmüller, Hanns [VerfasserIn]
Matentzoglu, Nicolas A [VerfasserIn]
Munoz-Torres, Monica C [VerfasserIn]
Schuetz, Catharina [VerfasserIn]
Seitz, Berthold [VerfasserIn]
Similuk, Morgan N [VerfasserIn]
Sparks, Teresa N [VerfasserIn]
Strauss, Timmy [VerfasserIn]
Swietlik, Emilia M [VerfasserIn]
Thompson, Rachel [VerfasserIn]
Zhang, Xingmin Aaron [VerfasserIn]
Mungall, Christopher J [VerfasserIn]
Haendel, Melissa A [VerfasserIn]
Robinson, Peter N [VerfasserIn]

Links:

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Themen:

570
Biology

doi:

10.1101/2023.07.13.23292612

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

XBI040201937