Increasing evidence indicates that non-coding RNAs (ncRNAs) have emerged as essential factors in most biological processes through diverse mechanisms. However, the biological functions of most ncRNAs are still poorly understood. Here, we developed ncFN, a novel and comprehensive framework for ncRNA function annotation based on a global and heterogeneous biomolecular network. Specifically, we constructed a Global Interaction Network (GIN) by integrating ncRNA-ncRNA, ncRNA-protein coding gene (PCG), and PCG-PCG interactions. The GIN consists of 565,482 edges connecting 17,060 PCGs and 12,616 ncRNAs, including 1095 microRNAs (miRNAs), 3563 long non-coding RNAs (lncRNAs), and 7958 circular RNAs (circRNAs). For each ncRNA, we quantified Association Strengths (ASs) between the ncRNA and PCGs through Random Walk with Restart in GIN. Then, Gene Set Enrichment Analysis was performed with ASs as input to annotate the function of the ncRNA. Compared to most conventional methods that only focus on a single ncRNA type, ncFN offers significant advantages in covering diverse ncRNA types and a larger number of ncRNA molecules. Moreover, we demonstrated the superiority of ncFN by comparing it with other methods in the annotation of well-acknowledged disease-relevant ncRNAs and differentially expressed ncRNAs in diseases. Finally, ncFN also facilitated enrichment analysis with multiple ncRNAs or pathways as input. In conclusion, ncFN is a comprehensive and reliable tool for functional annotation of miRNAs, lncRNAs, and circRNAs, making it highly suitable for widespread use in ncRNA research. ncFN is freely accessible at http://www.jianglab.cn/ncFN/, and all codes are deposited on GitHub (https://github.com/LongMin0705/ncFN).
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