Predicting the Functions of Long Noncoding RNAs Using RNA-Seq Based on Bayesian Network. (28th February 2015)
- Record Type:
- Journal Article
- Title:
- Predicting the Functions of Long Noncoding RNAs Using RNA-Seq Based on Bayesian Network. (28th February 2015)
- Main Title:
- Predicting the Functions of Long Noncoding RNAs Using RNA-Seq Based on Bayesian Network
- Authors:
- Xiao, Yun
Lv, Yanling
Zhao, Hongying
Gong, Yonghui
Hu, Jing
Li, Feng
Xu, Jinyuan
Bai, Jing
Yu, Fulong
Li, Xia - Other Names:
- Akutsu Tatsuya Academic Editor.
- Abstract:
- Abstract : Long noncoding RNAs (lncRNAs) have been shown to play key roles in various biological processes. However, functions of most lncRNAs are poorly characterized. Here, we represent a framework to predict functions of lncRNAs through construction of a regulatory network between lncRNAs and protein-coding genes. Using RNA-seq data, the transcript profiles of lncRNAs and protein-coding genes are constructed. Using the Bayesian network method, a regulatory network, which implies dependency relations between lncRNAs and protein-coding genes, was built. In combining protein interaction network, highly connected coding genes linked by a given lncRNA were subsequently used to predict functions of the lncRNA through functional enrichment. Application of our method to prostate RNA-seq data showed that 762 lncRNAs in the constructed regulatory network were assigned functions. We found that lncRNAs are involved in diverse biological processes, such as tissue development or embryo development (e.g., nervous system development and mesoderm development). By comparison with functions inferred using the neighboring gene-based method and functions determined using lncRNA knockdown experiments, our method can provide comparable predicted functions of lncRNAs. Overall, our method can be applied to emerging RNA-seq data, which will help researchers identify complex relations between lncRNAs and coding genes and reveal important functions of lncRNAs.
- Is Part Of:
- BioMed research international. Volume 2015(2015)
- Journal:
- BioMed research international
- Issue:
- Volume 2015(2015)
- Issue Display:
- Volume 2015, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 2015
- Issue:
- 2015
- Issue Sort Value:
- 2015-2015-2015-0000
- Page Start:
- Page End:
- Publication Date:
- 2015-02-28
- Subjects:
- Medicine -- Periodicals
Biology -- Periodicals
Biotechnology -- Periodicals
Life sciences -- Periodicals
610.5 - Journal URLs:
- https://www.hindawi.com/journals/bmri/ ↗
- DOI:
- 10.1155/2015/839590 ↗
- Languages:
- English
- ISSNs:
- 2314-6133
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23498.xml