The project aims to develop novel computational methods and tools to study microRNA binding interactions and microRNAs' role in gene regulation. Small (~22 nucleotide), non-coding RNAs called microRNAs have been known to regulate genes involved in key aspects of animal development and physiology through binding-interactions with their mRNA targets. Since the first discovery of microRNAs in C. elegans in 1993, a large number of microRNAs have been discovered in metazoan, plants and viruses. Today, microRNAs are known to express ubiquitously in almost all cell types, evolutionarily conserved in most of metazoan and plant species, and potentially regulate more than 30% of mammalian gene products. Understanding of microRNAs' regulatory functions in the fundamental biological processes is thus essential towards gaining a global view of gene regulation, but still at its early stages despite the rapid advances in microRNA biology. The project to study microRNA gene regulation and phenotype development seeks to generate many computational algorithms, which will be converted into software tools. These tools will be subsequently released as open-source and freely available software packages to the scientific community. The research is expected to have great impact on education at all levels.
The research will be incorporated into graduate, undergraduate and K-12 education. The research will also be disseminated to the research community, informal science education, and the public to enhance scientific understanding through freely distributed computational tools and web dissemination. In addition, mentoring and outreach for women and girls is planned to help attract more women into interdisciplinary science.
RNA is emerging as an important part of gene regulatory mechanisms under various phenotypic conditions. With the current unprecedented availability of genome-scale RNA genomics and transcriptomics data, the project seeks to create a set of computational algorithms and statistical methods to model microRNA binding interactions and discover microRNA interaction patterns that will help elucidate many functional roles of microRNAs in gene regulation. The advanced probabilistic model of microRNA binding activities promises to greatly benefit mRNA target recognition under specific phenotypic conditions, lay the foundation for further study of inter-microRNA interactions, and provide insight into microRNAs' functional mechanisms in gene regulation and phenotype formulation. The research is expected to not only advance scientific understanding of microRNAs' role in global gene regulation and phenotype development, but also stimulate interest in developing and advancing efficient computational modeling and data integration methods in the informatics research field. The research information and products will be made available through the project website (http://hulab.ucf.edu/research/projects/miRNA/).
