Mining statistically significant target mRNA association rules based on microRNA

Authors:
Feng Chen;Tingting Wang;Yu Wang;Shengfei Li;Jing Wang
Affiliations:
College of Information Science and Engineering, Henan University of Technology, China,School of Engineering and Mathematical Sciences, La Trobe University, Australia;School of Engineering and Mathematical Sciences, La Trobe University, Australia;College of Information Science and Engineering, Henan University of Technology, China;College of Information Science and Engineering, Henan University of Technology, China;Puyang Branch Company, Henan Electric Power Company, China
Venue:
IUKM'13 Proceedings of the 2013 international conference on Integrated Uncertainty in Knowledge Modelling and Decision Making
Year:
2013

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Abstract

The relation of miRNA and mRNA are very important because miRNA can regulate almost all the biological process by cooperating with mRNA. However, the directed regulation among mRNA has not been concerned a lot. In this paper, we introduce association rule mining and hypothesis test to find the closely related mRNAs and their regulation direction based on their relation with miRNAs. Our research can further the understanding about miRNA and mRNA. Our results uncover the novel mRNA association patterns, which could not only help to construct the biological network, but also extend the application of association rule mining in bioinformatics.