MDAPlatform: A Component-based Platform for Constructing and Assessing miRNA-disease Association Prediction Methods

Background: Increasing evidence has indicated that miRNA-disease association prediction plays a critical role in the study of clinical drugs. Researchers have proposed many computational models for miRNA-disease prediction. However, there is no unified platform to compare and analyze the pros and cons or share the code and data of these models. Objective: In this study, we developed an easy-to-use platform (MDAPlatform) to construct and assess miRNA-disease association prediction method. Methods: MDAPlatform integrates the relevant data of miRNA, disease and miRNA-disease associations that are used in previous miRNA-disease association prediction studies. Based on the componentized model, it develops different components of previous computational methods. Results: Users can conduct cross validation experiments and compare their methods with other methods, and the visualized comparison results are also provided. Conclusion: Based on the componentized model, MDAPlatform provides easy-to-operate interfaces to construct the miRNA-disease association method, which is beneficial to develop new miRNA-disease association prediction methods in the future.
Funding Information
  • Science and Technology Foundation of Guizhou, Province of China ([2020] 1Y264)
  • Hunan Provincial Science and Technology Program (2018 WK4001)
  • 111 Project (B18059)
  • NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (U1909208)
  • National Natural Science Foundation of China (61772552, 61962050)