Abstract
In recent years, numerous studies have demonstrated that circRNAs play crucial biological roles through their capacity to encode functional proteins. Computational methods have become essential for investigating circRNA translation. In this review, we first outline circRNA biogenesis and translation mechanisms to establish the rationale for developing specialized computational strategies. We then summarize experimental techniques and existing databases that support computational method development. Subsequently, we provide a systematic introduction to existing circRNA translation analysis tools and their underlying algorithms, with emphasis on benchmarking the performance of sequence-based methods using a unified dataset. Our benchmarking revealed that: (1) cirCodAn achieved superior predictive accuracy while maintaining user accessibility; (2) the training data selection during method development critically impacts model performance. This review serves as a comprehensive reference for the selection and application of circRNA translation analysis methods and provides foundational guidance for the development and refinement of future computational tools.