GPACDA: circRNA-disease association prediction with generating polynomials

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023736%3A_____%2F24%3A00013712" target="_blank" >RIV/00023736:_____/24:00013712 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-64629-4_3" target="_blank" >https://doi.org/10.1007/978-3-031-64629-4_3</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-64629-4_3" target="_blank" >10.1007/978-3-031-64629-4_3</a>

Result language
angličtina
Original language name
GPACDA: circRNA-disease association prediction with generating polynomials
Original language description
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.
Czech name
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Czech description
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Project
<a href="/en/project/NU20-03-00412" target="_blank" >NU20-03-00412: Role of transposable elements and PIWI-interacting RNAs in myelodysplastic syndrome and their potential clinical applications</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Book/collection name
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-303164628-7
Number of pages of the result
16
Pages from-to
33-48
Number of pages of the book
337
Publisher name
Springer Verlag
Place of publication
Berlin
UT code for WoS chapter
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