BNO—An ontology for understanding the transittability of complex biomolecular networks

Ayadi, A.; Zanni-Merk, Cécilia; Beuvron, François de Bertrand de; Thompson, Julie; Krichen, Saoussen

doi:10.1016/j.websem.2019.01.002

Cited by 2 publications

(1 citation statement)

References 44 publications

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“…It is crucial to evaluate a newly developed ontology before its publication or application, to ensure that it is complete with respect to the requirements for its intended application ( 45 , 46 ) and that it is consistent both from a logical standpoint (explanation consistency) and with respect to good practices in ontology design (structural consistency) ( 16 , 53–56 ).…”

Section: Introductionmentioning

confidence: 99%

The Immunopeptidomics Ontology (ImPO)

Faria,

Eugénio,

Contreiras Silva

et al. 2024

Database

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The adaptive immune response plays a vital role in eliminating infected and aberrant cells from the body. This process hinges on the presentation of short peptides by major histocompatibility complex Class I molecules on the cell surface. Immunopeptidomics, the study of peptides displayed on cells, delves into the wide variety of these peptides. Understanding the mechanisms behind antigen processing and presentation is crucial for effectively evaluating cancer immunotherapies. As an emerging domain, immunopeptidomics currently lacks standardization—there is neither an established terminology nor formally defined semantics—a critical concern considering the complexity, heterogeneity, and growing volume of data involved in immunopeptidomics studies. Additionally, there is a disconnection between how the proteomics community delivers the information about antigen presentation and its uptake by the clinical genomics community. Considering the significant relevance of immunopeptidomics in cancer, this shortcoming must be addressed to bridge the gap between research and clinical practice. In this work, we detail the development of the ImmunoPeptidomics Ontology, ImPO, the first effort at standardizing the terminology and semantics in the domain. ImPO aims to encapsulate and systematize data generated by immunopeptidomics experimental processes and bioinformatics analysis. ImPO establishes cross-references to 24 relevant ontologies, including the National Cancer Institute Thesaurus, Mondo Disease Ontology, Logical Observation Identifier Names and Codes and Experimental Factor Ontology. Although ImPO was developed using expert knowledge to characterize a large and representative data collection, it may be readily used to encode other datasets within the domain. Ultimately, ImPO facilitates data integration and analysis, enabling querying, inference and knowledge generation and importantly bridging the gap between the clinical proteomics and genomics communities. As the field of immunogenomics uses protein-level immunopeptidomics data, we expect ImPO to play a key role in supporting a rich and standardized description of the large-scale data that emerging high-throughput technologies are expected to bring in the near future. Ontology URL: https://zenodo.org/record/10237571 Project GitHub: https://github.com/liseda-lab/ImPO/blob/main/ImPO.owl

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Section: Introductionmentioning

confidence: 99%

The Immunopeptidomics Ontology (ImPO)

Faria,

Eugénio,

Contreiras Silva

et al. 2024

Database

View full text Add to dashboard Cite

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An ontology for defining and characterizing demonstration environments

Nie,

De Vita,

Masood

2023

J Intell Manuf

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Demonstration Environments (DEs) are essential tools for testing and demonstrating new technologies, products, and services, and reducing uncertainties and risks in the innovation process. However, the terminology used to describe these environments is inconsistent, leading to heterogeneity in defining and characterizing them. This makes it difficult to establish a universal understanding of DEs and to differentiate between the different types of DEs, including testbeds, pilot-plants, and living labs. Moreover, existing literature lacks a holistic view of DEs, with studies focusing on specific types of DEs and not offering an integrated perspective on their characteristics and applicability in different contexts. This study proposes an ontology for knowledge representation related to DEs to address this gap. Using an ontology learning approach analyzing 3621 peer-reviewed journal articles, we develop a standardized framework for defining and characterizing DEs, providing a holistic view of these environments. The resulting ontology allows innovation managers and practitioners to select appropriate DEs for achieving their innovation goals, based on the characteristics and capabilities of the specific type of DE. The contributions of this study are significant in advancing the understanding and application of DEs in innovation processes. The proposed ontology provides a standardized approach for defining and characterizing DEs, reducing inconsistencies in terminology and establishing a common understanding of these environments. This enables innovation managers and practitioners to select appropriate DEs for their specific innovation goals, facilitating more efficient and effective innovation processes. Overall, this study provides a valuable resource for researchers, practitioners, and policymakers interested in the effective use of DEs in innovation.

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BNO—An ontology for understanding the transittability of complex biomolecular networks

Cited by 2 publications

References 44 publications

The Immunopeptidomics Ontology (ImPO)

The Immunopeptidomics Ontology (ImPO)

An ontology for defining and characterizing demonstration environments

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