ArticleNon-coding RNA research2026
ncFN: a comprehensive non-coding RNA function annotation framework based on a global and heterogeneous biomolecular network.
Article in Non-coding RNA research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.