Biomedical ontologies have been growing quickly and proven to be useful in many biomedical applications. The use of these data is mainly based on semantic similarity calculation between ontology terms and between annotated biomedical entities. In addition, they are also used in enrichment analyses. Many semantic similarity calculation and enrichment analysis methods have been proposed for such the tasks. A number of tools have been developed on different platforms for semantic similarity calculation, enrichment analysis and ontology visualization. However, these tools have implemented a small number of the semantic similarity calculation and enrichment analysis methods for a certain type of biomedical ontology. Note that, the methods can be applied to all types of biomedical ontologies. In addition, each method is dominant in different biomedical applications.
In this study, we developed a Cytoscape app, named UFO, which unifies most of the semantic similarity measures for similarity calculation for all types of biomedical ontologies. Based on the similarity calculation, UFO can calculate the similarity between two sets of entities and weigh imported entity networks as well as generate functional similarity networks. In addition, it can perform enrichment analysis of a set of entities by different methods. Moreover, UFO can visualize structural relationships between ontology terms, annotating relationships between entities and terms, and functional similarity between entities. Finally, we demonstrated the ability of UFO through a number of case studies on finding the best semantic similarity measures for assessing the similarity between human disease phenotypes and on constructing gene and protein complex similarity networks for predicting disease-associated biomarkers.
Taken together, UFO is expected to be a tool where biomedical ontologies can be exploited for various biomedical applications.