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Random Forest model reveals the interaction between N6-methyladenosine modifications and RNA-binding proteins.
Hong, Wei; Zhao, Yanding; Weng, Yi-Lan; Cheng, Chao.
Afiliación
  • Hong W; Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA.
  • Zhao Y; Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA.
  • Weng YL; Center for Neuroregeneration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX 77030, USA.
  • Cheng C; Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA.
iScience ; 26(3): 106250, 2023 Mar 17.
Article en En | MEDLINE | ID: mdl-36922995
ABSTRACT
RNA-binding proteins (RBPs) have critical roles in N6-methyladenosine (m6A) modification process. We designed a Random Forest (RF) model to systematically analyze the interaction among RBPs and m6A modifications by integrating the binding signals from hundreds of RBPs. Accurate prediction of m6A sites demonstrated significant connections between RBP bindings and m6A modifications. The relative importance of different RBPs from the model provided a quantitative metric to evaluate their interactions with m6A modifications. Redundancy analysis showed that several RBPs may have similar binding patterns with m6A sites. The RF model exhibited fairly high prediction accuracy across cell lines, suggesting a conservative RBP interaction network regulates m6A occupancy. Specific RBPs can engage to the corresponding regional m6A sites and deploy distinct regulatory processes, such as cleavage site selection of the alternative polyadenylation (APA). We also integrated histone modifications into our RF model, which demonstrated H3K36me3 and H3K27me3 as determining features for m6A distribution.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies Idioma: En Revista: IScience Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies Idioma: En Revista: IScience Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos