: The purpose of the study described in this paper is to shed more light on disease similarities by analyzing the relationship between categorical proximity of diseases in human-curated ontologies and structural proximity of the related disease module (DM) in the interactome. We propose a methodology (and related algorithms) to automatically induce a hierarchical structure from proximity relations between DMs, and to compare this structure with a human-curated disease taxonomy.Clinical relevance- Disease ontologies are extensively used for diagnostic evaluation and clinical decision support but still reflect the clinical reductionist perspective. We demonstrate that the proposed network-based methodology allows us to analyze commonalities and differences among structural and categorical similarity of human diseases, help refine human disease classification systems, and identify promising network areas where new disease-gene interactions can be discovered.

Integrating categorical and structural proximity in Disease Ontologies / Madeddu, Lorenzo; Grani, Giorgio; Velardi, Paola. - 2021(2021), pp. 2011-2014-2014. ((Intervento presentato al convegno 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) tenutosi a Guadalajara, Mexico [10.1109/EMBC46164.2021.9630114].

Integrating categorical and structural proximity in Disease Ontologies

Madeddu, Lorenzo
Primo
;
Grani, Giorgio
Secondo
;
Velardi, Paola
Ultimo
2021

Abstract

: The purpose of the study described in this paper is to shed more light on disease similarities by analyzing the relationship between categorical proximity of diseases in human-curated ontologies and structural proximity of the related disease module (DM) in the interactome. We propose a methodology (and related algorithms) to automatically induce a hierarchical structure from proximity relations between DMs, and to compare this structure with a human-curated disease taxonomy.Clinical relevance- Disease ontologies are extensively used for diagnostic evaluation and clinical decision support but still reflect the clinical reductionist perspective. We demonstrate that the proposed network-based methodology allows us to analyze commonalities and differences among structural and categorical similarity of human diseases, help refine human disease classification systems, and identify promising network areas where new disease-gene interactions can be discovered.
978-1-7281-1179-7
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11573/1594458
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