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BMC Bioinformatics. 2018 Oct 16;19(1):379. doi: 10.1186/s12859-018-2410-0.

Discovering the 'Dark matters' in expression data of miRNA based on the miRNA-mRNA and miRNA-lncRNA networks.

Author information

1
Ministry of Agriculture Key Lab of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Science, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
2
Department of Mathematics, College of Science, Nanjing Agricultural University, Nanjing, 210095, Jiangsu, China.
3
Analysis Center of Agrobiology and Environmental Sciences, Zhejiang University, Hangzhou, 310058, Zhejiang, China.
4
Ministry of Agriculture Key Lab of Molecular Biology of Crop Pathogens and Insects, Institute of Insect Science, Zhejiang University, Hangzhou, 310058, Zhejiang, China. lifei18@zju.edu.cn.

Abstract

BACKGROUND:

Since miRNAs can play important roles in different cancer types, how to discover cancer related miRNAs is an important issue. In general, the miRNAs with differential expression is the focus of attention. However, some important cancer related miRNAs are not excavated by differential expression analysis. We take this type of miRNAs as 'dark matters' (DM-miRNA). It is our great interests to develop an algorithm to discover DM-miRNAs.

RESULTS:

An effective method was developed to find DM-miRNAs. This method is mainly for mining potential DM-miRNAs by building basic miRNA-mRNA network (BMMN) and miRNA-lncRNA network (BMLN). The results indicate that miRNA-mRNA and miRNA-lncRNA interactions can be used as novel cancer biomarkers.

CONCLUSIONS:

The BMMN and BMLN can excavate the non-differentially expressed miRNAs which play an important role in the cancer. What's more, the edge biomarkers (miRNA-mRNA and miRNA-lncRNA interactions) contain more information than the node biomarkers. It will contribute to developing novel therapeutic candidates in cancers.

KEYWORDS:

Biomarkers; Dark matters; miRNA-lncRNA network; miRNA-mRNA network

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