Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies

Alghamdi, Sarah M.; Sundberg, Beth A.; Sundberg, John P.; Schofield, Paul N.; Hoehndorf, Robert

doi:10.1101/378927

Cited by 4 publications

(4 citation statements)

References 45 publications

(46 reference statements)

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“…2,3 Vascular lesions were coded to the Mouse Pathology (MPATH) and Mouse Anatomy (MA) ontologies as previously described, 29,33 and anatomical location and pathological diagnoses were combined into the precomposed PAM ontology, which classifies lesions from MPATH by anatomical site using the MA ontology. 1 Overrepresentation was calculated using the Ontofunc and Func tools 14 as described previously. 1 We performed a hypergeometric test to establish the strains in which vascular lesions are overrepresented.…”

Section: Methodsmentioning

confidence: 99%

“…1 Overrepresentation was calculated using the Ontofunc and Func tools 14 as described previously. 1 We performed a hypergeometric test to establish the strains in which vascular lesions are overrepresented. The P value obtained indicates which strains and sex have disproportionately frequent vascular lesions of all types with respect to all the strains examined.…”

Section: Methodsmentioning

confidence: 99%

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Hyaline Arteriolosclerosis in 30 Strains of Aged Inbred Mice

et al. 2019

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During a screen for vascular phenotypes in aged laboratory mice, a unique discrete phenotype of hyaline arteriolosclerosis of the intertubular arteries and arterioles of the testes was identified in several inbred strains. Lesions were limited to the testes, and did not occur as part of any renal, systemic, or pulmonary arteriopathy or vasculitis phenotype. There was no evidence of systemic or pulmonary hypertension, and lesions did not occur in female ovaries. Frequency was highest in males of the SM/J (27/30, 90%) and WSB/EiJ (19/26, 73%) strains, aged 383 to 847 days. Lesions were sporadically present in males from several other inbred strains at a much lower (<20%) frequency. The risk of testicular hyaline arteriolosclerosis is at least partially underpinned by a genetic predisposition which is not associated with other vascular lesions (including vasculitis), separating out the etiology of this form and site of arteriolosclerosis from other related conditions that often co-occur in other strains of mice and in humans. Because of their genetic uniformity and controlled dietary and environmental conditions, mice are an excellent model to dissect the pathogenesis of human disease conditions. In this study a discrete genetically driven phenotype of testicular hyaline arteriolosclerosis in aging mice was identified. These observations open the possibility of identifying the underlying genetic variant(s) associated with the predisposition and therefore allowing future interrogation of the pathogenesis of this condition. AbstractDuring a screen for vascular phenotypes in aged laboratory mice, a unique discrete phenotype of hyaline arteriolosclerosis of the intertubular arteries and arterioles of the testes was identified in several inbred strains. Lesions were limited to the testes, and did not occur as part of any renal, systemic, or pulmonary arteriopathy or vasculitis phenotype. There was no evidence of systemic or pulmonary hypertension, and lesions did not occur in female ovaries. Frequency was highest in males of the SM/J (27/30, 90%) and WSB/EiJ (19/26, 73%) strains, aged 383 to 847 days. Lesions were sporadically present in males from several other inbred strains at a much lower (<20%) frequency. The risk of testicular hyaline arteriolosclerosis is at least partially underpinned by a genetic predisposition which is not associated with other vascular lesions (including vasculitis), separating out the etiology of this form and site of arteriolosclerosis from other related conditions that often co-occur in other strains of mice and in humans. Because of their genetic uniformity and controlled dietary and environmental conditions, mice are an excellent model to dissect the pathogenesis of human disease conditions. In this study a discrete genetically driven phenotype of testicular hyaline arteriolosclerosis in aging mice was identified. These observations open the possibility of identifying the underlying genetic variant(s) associated with the predisposition and therefore allowing future interrogation of the...

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Hyaline Arteriolosclerosis in 30 Strains of Aged Inbred Mice

et al. 2019

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“…In Internet of Things (IoT) environments, ensuring interoperability is challenging due to the heterogeneous nature of data from devices like health and fitness trackers. Proprietary formats and lack of common terms often lead to certain challenges related to communication protocols and data formats [10]. Overcoming these challenges requires adopting common syntax and semantics for IoT-generated data.…”

Section: Symbolic Ai and Ontology Engineeringmentioning

confidence: 99%

Evaluating Ontology-Based PD Monitoring and Alerting in Personal Health Knowledge Graphs and Graph Neural Networks

Zafeiropoulos,

Bitilis,

Tsekouras

et al. 2024

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In the realm of Parkinson’s Disease (PD) research, the integration of wearable sensor data with personal health records (PHR) has emerged as a pivotal avenue for patient alerting and monitoring. This study delves into the complex domain of PD patient care, with a specific emphasis on harnessing the potential of wearable sensors to capture, represent and semantically analyze crucial movement data and knowledge. The primary objective is to enhance the assessment of PD patients by establishing a robust foundation for personalized health insights through the development of Personal Health Knowledge Graphs (PHKGs) and the employment of personal health Graph Neural Networks (PHGNNs) that utilize PHKGs. The objective is to formalize the representation of related integrated data, unified sensor and PHR data in higher levels of abstraction, i.e., in a PHKG, to facilitate interoperability and support rule-based high-level event recognition such as patient’s missing dose or falling. This paper, extending our previous related work, presents the Wear4PDmove ontology in detail and evaluates the ontology within the development of an experimental PHKG. Furthermore, this paper focuses on the integration and evaluation of PHKG within the implementation of a Graph Neural Network (GNN). This work emphasizes the importance of integrating PD-related data for monitoring and alerting patients with appropriate notifications. These notifications offer health experts precise and timely information for the continuous evaluation of personal health-related events, ultimately contributing to enhanced patient care and well-informed medical decision-making. Finally, the paper concludes by proposing a novel approach for integrating personal health KGs and GNNs for PD monitoring and alerting solutions.

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“…Over the past years, significant efforts have been made to enrich ontologies by incorporating formalized background knowledge as well as meta-data that improve accessibility and utility of the ontologies (Smith et al, 2007;Mungall et al, 2011). Incorporation of formal axioms contributes to detecting whether ontologies are consistent (Smith et al, 2003;Smith and Brochhausen, 2010;Stevens et al, 2003), enables automated reasoning and expressive queries (Hoehndorf et al, 2015a;da Silva et al, 2017;Jupp et al, 2012), facilitates connecting and integrating ontologies of different domains through the application of ontology design patterns (Osumi-Sutherland et al, 2017;Hoehndorf et al, 2010), and can be used to guide ontology development (Köhler et al, 2013;Alghamdi et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Formal axioms in biomedical ontologies improve analysis and interpretation of associated data

Smaili

Gao

Hoehndorf

2019

Preprint

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Motivation:There are now over 500 ontologies in the life sciences. Over the past years, significant resources have been invested into formalizing these biomedical ontologies. Formal axioms in ontologies have been developed and used to detect and ensure ontology consistency, find unsatisfiable classes, improve interoperability, guide ontology extension through the application of axiom-based design patterns, and encode domain background knowledge. At the same time, ontologies have extended their amount of human-readable information such as labels and definitions as well as other meta-data. As a consequence, biomedical ontologies now form large formalized domain knowledge bases and have a potential to improve ontology-based data analysis by providing background knowledge and relations between biological entities that are not otherwise connected. Results: We evaluate the contribution of formal axioms and ontology meta-data to the ontology-based prediction of protein-protein interactions and gene-disease associations. We find that the formal axioms that have been created for the Gene Ontology and several other ontologies significantly improve ontologybased prediction models through provision of domain-specific background knowledge. Furthermore, we find that the labels, synonyms and definitions in ontologies can also provide background knowledge that may be exploited for prediction. The axioms and meta-data of different ontologies contribute in varying degrees to improving data analysis. Our results have major implications on the further development of formal knowledge bases and ontologies in the life sciences, in particular as machine learning methods are more frequently being applied. Our findings clearly motivate the need for further development, and the systematic, application-driven evaluation and improvement, of formal axioms in ontologies. Availability: https://

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Quantitative evaluation of ontology design patterns for combining pathology and anatomy ontologies

Cited by 4 publications

References 45 publications

Hyaline Arteriolosclerosis in 30 Strains of Aged Inbred Mice

Hyaline Arteriolosclerosis in 30 Strains of Aged Inbred Mice

Evaluating Ontology-Based PD Monitoring and Alerting in Personal Health Knowledge Graphs and Graph Neural Networks

Formal axioms in biomedical ontologies improve analysis and interpretation of associated data

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