Predictions are primarily based on base pairings in the miRNA seed region (the first eight nucleotides of an miRNA), conservation of target sites across species, accessibility of target sites, free energy of the miRNA–mRNA duplex, or a combination of two or more of these features (3,14). Complementing experimental data, a large number of computational methods have been developed to predict potential miRNA targets (6–13). Many experimental approaches have been utilized to identify and validate miRNA targets (4,5). With more than 60% of human 3’-UTRs under evolutionary pressure to maintain conserved miRNA target sites (2), miRNAs could play roles in most, if not all, biological processes (3). INTRODUCTION microRNAs (miRNAs) with proven biological functions are involved in biological processes in all organs of the human body (1), including cell cycle control, cell survival, drug resistance and many tissue specific activities.
We also demonstrate how multiMiR was used to generate testable hypotheses that were pursued experimentally.
Case studies are reported on various biomedical applications including mouse models of alcohol consumption, studies of chronic obstructive pulmonary disease in human subjects, and human cell line models of bladder cancer metastasis. We present multiMiR, a new miRNA–target interaction R package and database, which includes several novel features not available in existing R packages: (i) compilation of nearly 50 million records in human and mouse from 14 different databases, more than any other collection (ii) expansion of databases to those based on disease annotation and drug microRNA response, in addition to many experimental and computational databases and (iii) user-defined cutoffs for predicted binding strength to provide the most confident selection. Currently available miRNA target site packages in R are limited in the number of databases, types of databases and flexibility. Several online resources provide collections of multiple databases but need to be imported into other software, such as R, for processing, tabulation, graphing and computation. miRNA target sites have been catalogued in databases based on experimental validation and computational prediction using various algorithms. Abstract microRNAs (miRNAs) regulate expression by promoting degradation or repressing translation of target transcripts.
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