ABI Innovation: Computational Analysis of microRNA Binding

该项目旨在开发新的计算方法和工具来研究microRNA结合相互作用和microRNA在基因调控中的作用。小的（约22个核苷酸），非编码rna，被称为microrna，通过与mRNA靶标的结合相互作用来调节参与动物发育和生理关键方面的基因。自1993年在秀丽隐杆线虫中首次发现microrna以来，在后生动物、植物和病毒中相继发现了大量microrna。今天，已知microrna在几乎所有细胞类型中普遍表达，在大多数后生动物和植物物种中进化保守，并可能调节超过30%的哺乳动物基因产物。因此，了解microRNA在基本生物学过程中的调控功能对于获得基因调控的全局视图至关重要，但尽管microRNA生物学进展迅速，但仍处于早期阶段。研究microRNA基因调控和表型发育的项目寻求生成许多计算算法，这些算法将转化为软件工具。这些工具随后将作为开源和免费提供的软件包发布给科学界。预计该研究将对各级教育产生重大影响。这项研究将被纳入研究生、本科和K-12教育。该研究还将通过免费分发的计算工具和网络传播，向研究界、非正式科学教育和公众传播，以增进科学理解。此外，计划为妇女和女孩提供指导和外联，以帮助吸引更多妇女进入跨学科科学。RNA正在成为各种表型条件下基因调控机制的重要组成部分。随着目前前所未有的基因组级RNA基因组学和转录组学数据的可用性，该项目寻求创建一套计算算法和统计方法来模拟microRNA结合相互作用，并发现microRNA相互作用模式，这将有助于阐明microRNA在基因调控中的许多功能角色。先进的microRNA结合活性概率模型有望极大地促进特定表型条件下的mRNA靶标识别，为进一步研究microRNA间相互作用奠定基础，并深入了解microRNA在基因调控和表型形成中的功能机制。该研究不仅有望促进对microRNAs在全球基因调控和表型发育中的作用的科学理解，而且还将激发人们对信息学研究领域开发和推进高效计算建模和数据集成方法的兴趣。研究信息和产品将通过项目网站（http://hulab.ucf.edu/research/projects/miRNA/）提供。

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/).