The microRNAs (miRNAs) are small non-coding RNAs that regulate the expression of protein-coding genes. Alterations of miRNA genes have been detected in many human tumors. MicroRNAs expression profiling has been exploited to identify miRNAs that are potentially involved in the pathogenesis of human cancers. Profiling has been allowed the definitions of signatures associated with diagnosis, staging, and progression and response to treatment of human tumors. In addition, profiling has been exploited to identify microRNAs genes that are downstream targets of activated oncogenic pathways or that are targeting protein coding genes involved in cancer.
Identification of miRNA targets is an overarching theme in the research of microRNAs. Normal random variation in sequence complementarity requires assessment of the strengths of putative targets. Experimentally validated and excluded targets are valuable for building machine learning tools for systematic target prediction and filtering. Such issues, among many others, are challenging yet provide great opportunities for statistical and bioinformatical research. Thus, one of the goals of this workshop is to bring interested statisticians to interact with biologists, the majority of the invited speakers, to tackle such, and many other problems in microRNA research.