Using Context-Sensitive Text Mining to Identify miRNAs in Different Stages of Atherosclerosis.

790 human and mouse micro-RNAs (miRNAs) are involved in diseases. More than 26,428 miRNA-gene interactions are annotated in humans and mice. Most of these interactions are posttranscriptional regulations: miRNAs bind to the messenger RNAs (mRNAs) of genes and induce their degradation, thereby reducing the gene expression of target genes. For atherosclerosis, 667 miRNA-gene interactions for 124 miRNAs and 343 genes have been identified and described in numerous publications. Some interactions were observed through high-throughput experiments, others were predicted using bioinformatic methods, and some were determined by targeted experiments. Several reviews collect knowledge on miRNA-gene interactions in (specific aspects of) atherosclerosis.Here, we use our bioinformatics resource (atheMir) to give an overview of miRNA-gene interactions in the context of atherosclerosis. The interactions are based on public databases and context-based text mining of 28 million PubMed abstracts. The miRNA-gene interactions are obtained from more than 10,000 publications, of which more than 1,000 are in a cardiovascular disease context (266 in atherosclerosis). We discuss interesting miRNA-gene interactions in atherosclerosis, grouped by specific processes in different cell types and six phases of atherosclerotic progression. All evidence is referenced and easily accessible: Relevant interactions are provided by atheMir as supplementary tables for further evaluation and, for example, for the subsequent data analysis of high-throughput measurements as well as for the generation and validation of hypotheses. The atheMir approach has several advantages: (1) the evidence is easily accessible, (2) regulatory interactions are uniformly available for subsequent high-throughput data analysis, and (3) the resource can incrementally be updated with new findings. Georg Thieme Verlag KG Stuttgart · New York.