Abstract
Increasing evidence indicated that long non-coding RNAs (lncRNAs) were involved in various biological processes and complex diseases by communicating with mRNAs/miRNAs each other. Exploiting interactions between lncRNAs and mRNA/miRNAs to lncRNA functional similarity (LFS) is an effective method to explore function of lncRNAs and predict novel lncRNA-disease associations. In this article, we proposed an integrative framework, IntNetLncSim, to infer LFS by modeling the information flow in an integrated network that comprises both lncRNA-related transcriptional and post-transcriptional information. The performance of IntNetLncSim was evaluated by investigating the relationship of LFS with the similarity of lncRNA-related mRNA sets (LmRSets) and miRNA sets (LmiRSets). As a result, LFS by IntNetLncSim was significant positively correlated with the LmRSet (Pearson correlation γ2=0.8424) and LmiRSet (Pearson correlation γ2=0.2601). Particularly, the performance of IntNetLncSim is superior to several previous methods. In the case of applying the LFS to identify novel lncRNA-disease relationships, we achieved an area under the ROC curve (0.7300) in experimentally verified lncRNA-disease associations based on leave-one-out cross-validation. Furthermore, highly-ranked lncRNA-disease associations confirmed by literature mining demonstrated the excellent performance of IntNetLncSim. Finally, a web-accessible system was provided for querying LFS and potential lncRNA-disease relationships: http://www.bio-bigdata.com/IntNetLncSim.
Highlights
Recent large-scale genomic and transcriptomic analysis has shown that only less than 2% of genome sequence can encode protein, and functional non-coding transcripts constitute a large portion of the genome transcripts [1, 2]
lncRNA functional similarity (LFS) by IntNetLncSim was significant positively correlated with the lncRNA-related mRNA sets (LmRSets) (Pearson correlation γ2=0.8424) and LmiRSet (Pearson correlation γ2=0.2601)
IntNetLncSim functional similarity of long non-coding RNAs (lncRNAs) was significant positively correlated with the LmRSet (Pearson correlation γ2=0.8424, p=2.2e-16; Figure 1A) and LmiRSet (Pearson correlation γ2=0.2601, p=2.2e-16; Figure 1C)
Summary
Recent large-scale genomic and transcriptomic analysis has shown that only less than 2% of genome sequence can encode protein, and functional non-coding transcripts constitute a large portion of the genome transcripts [1, 2]. Long non-coding RNAs (lncRNAs), a recently discovered class of non-coding RNAs, was arbitrarily defined as mRNA-like transcripts longer than 200 nucleotides that have no or little protein-coding capacity [3]. The accumulating evidence suggested that lncRNAs are a novel and crucial layer of gene regulation network, and play important roles in various biological processes, such as imprinting, developmental regulation, chromatin modification, transcriptional regulation, dosage compensation and so on [3,4,5,6,7]. Only 182 functional lncRNAs were manually curated from existing literature in lncRNAdb [24]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
