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Micro-RNAs (miRNAs) are potent disease modulators due to their distinct interactions with specific genes in diseases and cell types. Most of these interactions are post-transcriptional regulations: miRNAs bind to the mRNA of genes and induce their degradation, thereby reducing the gene expression of target genes.
While there are many databases listing miRNA-gene interactions, retrieved from computational predictions or imputed from specific high-throughput data, most confirmation low-throughput experiments are published in text form. Hence, retrieving experimentally verified miRNA-gene interactions from literature, abstracts or full-texts, is an extremely important and useful task for assessing the actual miRNA-gene interaction landscape.
To derive the mx-plore database a newly developed text mining strategy combining dependency graph analysis and rule-based systems has been developed. Identified interactions are saved in a database along terms describing the context of the miRNA-gene interaction containing document. Our mx-plore platform makes the such identified miRNA-gene interactions accessible and searchable, even by cell type, disease or involved processes.