Circular RNAs (circRNAs), recognized as covalently closed, single-stranded RNA molecules formed through reverse splicing, are characterized by their unique ring structures, site-specific splicing, and tissue-specific expression. These molecules have garnered considerable interest due to their roles in gene regulation, development, and particularly in carcinogenesis. Extensive investigations have unveiled interactions between circRNAs and RNA-binding proteins (RBPs), highlighting their potential as biomarkers in cancer diagnosis and treatment. However, despite their promising applications, the vast majority of circRNAs and their functions in polygenic diseases remain largely unexplored, largely due to the constraints of experimental methodologies.
This Research Topic aims to showcase cutting-edge research on the association between circRNAs and diseases, particularly their utility in diagnosing and treating various disorders. By highlighting recent advancements and innovative computational methods developed to study circRNAs, this issue seeks to catalyze further research and clinical applications, ultimately contributing to the advancement of precision medicine and providing new avenues for cancer treatment.
To gather further insights in circRNA research within the realm of bioinformatics and medical sciences, we welcome articles addressing, but not limited to, the following themes:
Application of deep learning and machine learning for predicting circRNA associations with diseases
Bioinformatics tools and experimental validation of circRNA as cancer biomarkers
Use of deep learning to elucidate circRNA functions
Investigating the link between drug sensitivity and circRNA profiles
Circular RNAs (circRNAs), recognized as covalently closed, single-stranded RNA molecules formed through reverse splicing, are characterized by their unique ring structures, site-specific splicing, and tissue-specific expression. These molecules have garnered considerable interest due to their roles in gene regulation, development, and particularly in carcinogenesis. Extensive investigations have unveiled interactions between circRNAs and RNA-binding proteins (RBPs), highlighting their potential as biomarkers in cancer diagnosis and treatment. However, despite their promising applications, the vast majority of circRNAs and their functions in polygenic diseases remain largely unexplored, largely due to the constraints of experimental methodologies.
This Research Topic aims to showcase cutting-edge research on the association between circRNAs and diseases, particularly their utility in diagnosing and treating various disorders. By highlighting recent advancements and innovative computational methods developed to study circRNAs, this issue seeks to catalyze further research and clinical applications, ultimately contributing to the advancement of precision medicine and providing new avenues for cancer treatment.
To gather further insights in circRNA research within the realm of bioinformatics and medical sciences, we welcome articles addressing, but not limited to, the following themes:
Application of deep learning and machine learning for predicting circRNA associations with diseases
Bioinformatics tools and experimental validation of circRNA as cancer biomarkers
Use of deep learning to elucidate circRNA functions
Investigating the link between drug sensitivity and circRNA profiles