circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data
Abstract Circular RNAs play a crucial role in cell development and serve as biomarkers in many diseases. Nevertheless, the function of many circular RNAs remains unknown. This function can be inferred from sponging and silencing interactions with micro RNAs and messenger RNAs. We recently proposed a...
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BMC
2025-08-01
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| Series: | BioData Mining |
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| Online Access: | https://doi.org/10.1186/s13040-025-00468-3 |
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| author | Petr Ryšavý Alikhan Anuarbekov Michaela Dostálová Merkerová Jiří Kléma |
| author_facet | Petr Ryšavý Alikhan Anuarbekov Michaela Dostálová Merkerová Jiří Kléma |
| author_sort | Petr Ryšavý |
| collection | DOAJ |
| description | Abstract Circular RNAs play a crucial role in cell development and serve as biomarkers in many diseases. Nevertheless, the function of many circular RNAs remains unknown. This function can be inferred from sponging and silencing interactions with micro RNAs and messenger RNAs. We recently proposed a network-based circRNA functional annotation tool, circGPA. However, validation data for RNA interactions are often sparse and predicted interactions contain many false positives. To address this issue, we propose an extended algorithm named circGPAcorr, which uses expression data to weight the interactions, resulting in more precise functional annotation. To assess the significance of the results, the p-value is calculated using reduction to circGPA, a generating-polynomial-based method. We show that the problem is #P-hard, and thus computationally difficult. The circGPAcorr algorithm is tested on publicly available myelodysplastic syndromes expression data, providing gene ontology annotations that align with the literature on myelodysplastic syndromes. At the same time, we demonstrate its performance in the circRNA-disease annotation task. |
| format | Article |
| id | doaj-art-e6806ead8ccd47f2875c4032fe2be799 |
| institution | Kabale University |
| issn | 1756-0381 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | BMC |
| record_format | Article |
| series | BioData Mining |
| spelling | doaj-art-e6806ead8ccd47f2875c4032fe2be7992025-08-20T04:01:53ZengBMCBioData Mining1756-03812025-08-0118113210.1186/s13040-025-00468-3circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression dataPetr Ryšavý0Alikhan Anuarbekov1Michaela Dostálová Merkerová2Jiří Kléma3Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in PragueDepartment of Computer Science, Faculty of Electrical Engineering, Czech Technical University in PragueDepartment of Genomics, Institute of Hematology and Blood TransfusionDepartment of Computer Science, Faculty of Electrical Engineering, Czech Technical University in PragueAbstract Circular RNAs play a crucial role in cell development and serve as biomarkers in many diseases. Nevertheless, the function of many circular RNAs remains unknown. This function can be inferred from sponging and silencing interactions with micro RNAs and messenger RNAs. We recently proposed a network-based circRNA functional annotation tool, circGPA. However, validation data for RNA interactions are often sparse and predicted interactions contain many false positives. To address this issue, we propose an extended algorithm named circGPAcorr, which uses expression data to weight the interactions, resulting in more precise functional annotation. To assess the significance of the results, the p-value is calculated using reduction to circGPA, a generating-polynomial-based method. We show that the problem is #P-hard, and thus computationally difficult. The circGPAcorr algorithm is tested on publicly available myelodysplastic syndromes expression data, providing gene ontology annotations that align with the literature on myelodysplastic syndromes. At the same time, we demonstrate its performance in the circRNA-disease annotation task.https://doi.org/10.1186/s13040-025-00468-3Functional annotationCircRNAGenerating polynomialGene expression |
| spellingShingle | Petr Ryšavý Alikhan Anuarbekov Michaela Dostálová Merkerová Jiří Kléma circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data BioData Mining Functional annotation CircRNA Generating polynomial Gene expression |
| title | circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data |
| title_full | circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data |
| title_fullStr | circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data |
| title_full_unstemmed | circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data |
| title_short | circGPAcorr: an integrative tool for functional annotation of circular RNAs using expression data |
| title_sort | circgpacorr an integrative tool for functional annotation of circular rnas using expression data |
| topic | Functional annotation CircRNA Generating polynomial Gene expression |
| url | https://doi.org/10.1186/s13040-025-00468-3 |
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