About this document
SPRDA: Predicting Disease-Associated piRNAs by zhanjiayu472 is a document available to read on EtoBox.
The document presents SPRDA, a novel computational model for predicting disease-associated piwi-interacting RNAs (piRNAs) using structural perturbation methods. SPRDA demonstrates high performance in identifying piRNA-disease associations, achieving an AUC of 0.9529 in cross-validation, and provides insights into the mechanisms of disease, particularly in oncology. The study highlights the importance of piRNAs as biomarkers in cancer diagnosis and treatment, addressing the need for large-scale piRNA candida
- Author
- zhanjiayu472
- Language
- EN