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GPACDA – circRNA-Disease Association Prediction with Generating Polynomials

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Bioinformatics and Biomedical Engineering (IWBBIO 2024)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 14848))

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Abstract

Circular RNA, a molecule with partially understood functions, has been implicated in various diseases. Therefore, there is a vast effort to predict associations between circular RNAs and diseases. In our recent study, we introduced circGPA, an algorithm that enables the annotation of circular RNAs with gene ontology terms through interactions with miRNAs and mRNAs. Recognizing the analytical similarity in predicting disease associations, we developed GPACDA, an extension of circGPA tailored for disease associations. The benefits of our methods include explainability, as the outputs are based on known interactions and associations, as well as the rigorous calculation of the p-value, which the circGPA algorithm can compute. We compared our method with two other tools, NCPCDA and DWNCPCDA, using a subset of the CDASOR dataset and showed that GPACDA overcomes its competitors in terms of true association ranks. Our method’s code and predictions are publicly accessible.

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Acknowledgment

This work was supported by the Ministry of Health of the Czech Republic - Czech Health Research Council, grant AZV NU20-03-00412.

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Authors and Affiliations

  1. Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic

    Petr Ryšavý & Jiří Kléma

  2. Department of Genomics, Institute of Hematology and Blood Transfusion, Prague, Czech Republic

    Michaela Dostálová Merkerová

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  1. Petr Ryšavý
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  2. Jiří Kléma
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  3. Michaela Dostálová Merkerová
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Correspondence to Petr Ryšavý .

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Editors and Affiliations

  1. Department of Computer Architecture, CITIC-UGR - University of Granada, Granada, Granada, Spain

    Ignacio Rojas

  2. Department of Computer Architecture, CITIC-UGR - University of Granada, Granada, Granada, Spain

    Francisco Ortuño

  3. Department of Computer Architecture, CITIC-UGR - University of Granada, Granada, Granada, Spain

    Fernando Rojas

  4. Department of Computer Architecture, CITIC-UGR - University of Granada, Granada, Granada, Spain

    Luis Javier Herrera

  5. Department of Applied Mathematics, University of Granada, Granada, Granada, Spain

    Olga Valenzuela

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Ryšavý, P., Kléma, J., Merkerová, M.D. (2024). GPACDA – circRNA-Disease Association Prediction with Generating Polynomials. In: Rojas, I., Ortuño, F., Rojas, F., Herrera, L.J., Valenzuela, O. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2024. Lecture Notes in Computer Science(), vol 14848. Springer, Cham. https://doi.org/10.1007/978-3-031-64629-4_3

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  • DOI: https://doi.org/10.1007/978-3-031-64629-4_3

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