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• W2073764144 abstract "MicroRNAs (miRNAs) are post-transcriptional regulators of mRNA expression and are involved in numerous cellular processes. Consequently, miRNAs are an important component of gene regulatory networks and an improved understanding of miRNAs will further our knowledge of these networks. There is a many-to-many relationship between miRNAs and mRNAs because a single miRNA targets multiple mRNAs and a single mRNA is targeted by multiple miRNAs. However, most of the current methods for the identification of regulatory miRNAs and their target mRNAs ignore this biological observation and focus on miRNA-mRNA pairs. We propose a two-step method for the identification of many-to-many relationships between miRNAs and mRNAs. In the first step, we obtain miRNA and mRNA clusters using a combination of miRNA-target mRNA prediction algorithms and microarray expression data. In the second step, we determine the associations between miRNA clusters and mRNA clusters based on changes in miRNA and mRNA expression profiles. We consider the miRNA-mRNA clusters with statistically significant associations to be potentially regulatory and, therefore, of biological interest. Our method reduces the interactions between several hundred miRNAs and several thousand mRNAs to a few miRNA-mRNA groups, thereby facilitating a more meaningful biological analysis and a more targeted experimental validation." @default.
• W2073764144 created "2016-06-24" @default.
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• W2073764144 date "2011-03-06" @default.
• W2073764144 modified "2023-10-09" @default.
• W2073764144 title "Identification of microRNA-mRNA modules using microarray data" @default.
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• W2073764144 doi "https://doi.org/10.1186/1471-2164-12-138" @default.
• W2073764144 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3065435" @default.
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• W2073764144 hasPublicationYear "2011" @default.
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