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Combining Gene Expression and Interactions Data with miRNA Family Information for Identifying miRNA-mRNA Regulatory Modules

  • Dan Luo
  • Shu-Lin Wang
  • Jianwen Fang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10362)

Abstract

It is well known that microRNAs (miRNAs) play pivotal roles in gene expression, transcriptional regulation and other important biological processes. An impressive body of literature indicates that miRNAs and mRNAs work cooperatively to form an important part of gene regulatory modules which are extensively involved in cancer. However, with the accumulation of available data, it is a great challenge to identify cancer-related miRNA regulatory modules and uncover their precise regulatory mechanism. This paper proposed a novel computational framework by combining gene expression and interaction data with miRNA family information to identify miRNA-mRNA regulatory modules (GIFMRM), which was evaluated on three heterogeneous datasets. Literature survey, biological significance and functional enrichment analysis were used to validate the obtained results. The analysis results show that the modules identified are highly correlated with the biological conditions in their respective datasets, and they enrich in GO biological processes and KEGG pathways.

Keywords

miRNA-mRNA regulation modules Gene expression miRNA family 

Notes

Acknowledgement

This work was supported by the grants of the National Science Foundation of China (Grant Nos. 61472467, 61672011, and 61471169) and the Collaboration and Innovation Center for Digital Chinese Medicine of 2011 Project of Colleges and Universities in Hunan Province.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.College of Computer Science and Electronics EngineeringHunan UniversityChangshaChina
  2. 2.Biometric Research Branch, Division of Cancer Treatment and DiagnosisNational Cancer InstituteRockvilleUSA

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