4.7 Review

A survey of circular RNAs in complex diseases: databases, tools and computational methods

期刊

BRIEFINGS IN BIOINFORMATICS
卷 23, 期 1, 页码 -

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bib/bbab444

关键词

circular RNAs; complex diseases; circRNA-disease associations; databases; tools; computational model

资金

  1. National Natural Science Foundation of China [62002116]
  2. Hunan Provincial Natural Science Foundation of China [2020JJ5373]
  3. Scientific Research Fund of Hunan Provincial Education Department [20B348]
  4. Hunan Provincial Science & Technology Project Foundation [2018TP1018, 2018R53065]

向作者/读者索取更多资源

This review discusses the relationship between circular RNAs (circRNAs) and complex human diseases, particularly their involvement in cancer progression. It highlights the functions and characteristics of circRNAs, introduces representative circRNAs related to tumorigenesis, and investigates available databases and tools for circRNA-disease studies. The review also comprehensively reviews computational methods for predicting circRNA-disease associations and discusses challenges and future research in the field.
Circular RNAs (circRNAs) are a category of novelty discovered competing endogenous non-coding RNAs that have been proved to implicate many human complex diseases. A large number of circRNAs have been confirmed to be involved in cancer progression and are expected to become promising biomarkers for tumor diagnosis and targeted therapy. Deciphering the underlying relationships between circRNAs and diseases may provide new insights for us to understand the pathogenesis of complex diseases and further characterize the biological functions of circRNAs. As traditional experimental methods are usually time-consuming and laborious, computational models have made significant progress in systematically exploring potential circRNA-disease associations, which not only creates new opportunities for investigating pathogenic mechanisms at the level of circRNAs, but also helps to significantly improve the efficiency of clinical trials. In this review, we first summarize the functions and characteristics of circRNAs and introduce some representative circRNAs related to tumorigenesis. Then, we mainly investigate the available databases and tools dedicated to circRNA and disease studies. Next, we present a comprehensive review of computational methods for predicting circRNA-disease associations and classify them into five categories, including network propagating-based, path-based, matrix factorization-based, deep learning-based and other machine learning methods. Finally, we further discuss the challenges and future researches in this field.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据