simona: a comprehensive R package for semantic similarity analysis on bio-ontologies.

Autor: Gu Z; Molecular Precision Oncology Program, National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 280, Heidelberg, 69120, Germany. z.gu@dkfz.de.
Jazyk: angličtina
Zdroj: BMC genomics [BMC Genomics] 2024 Sep 16; Vol. 25 (1), pp. 869. Date of Electronic Publication: 2024 Sep 16.
DOI: 10.1186/s12864-024-10759-4
Abstrakt: Background: Bio-ontologies are keys in structuring complex biological information for effective data integration and knowledge representation. Semantic similarity analysis on bio-ontologies quantitatively assesses the degree of similarity between biological concepts based on the semantics encoded in ontologies. It plays an important role in structured and meaningful interpretations and integration of complex data from multiple biological domains.
Results: We present simona, a novel R package for semantic similarity analysis on general bio-ontologies. Simona implements infrastructures for ontology analysis by offering efficient data structures, fast ontology traversal methods, and elegant visualizations. Moreover, it provides a robust toolbox supporting over 70 methods for semantic similarity analysis. With simona, we conducted a benchmark against current semantic similarity methods. The results demonstrate methods are clustered based on their mathematical methodologies, thus guiding researchers in the selection of appropriate methods. Additionally, we explored annotation-based versus topology-based methods, revealing that semantic similarities solely based on ontology topology can efficiently reveal semantic similarity structures, facilitating analysis on less-studied organisms and other ontologies.
Conclusions: Simona offers a versatile interface and efficient implementation for processing, visualization, and semantic similarity analysis on bio-ontologies. We believe that simona will serve as a robust tool for uncovering relationships and enhancing the interoperability of biological knowledge systems.
(© 2024. The Author(s).)
Databáze: MEDLINE
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