MCA: A Computational Framework to Study microRNAs in Cell-Cell Interactions

细胞间的相互作用对多细胞生物的整体功能至关重要。最近的研究发现，非编码microrna （mirna）可以从一个细胞转移到另一个细胞，以执行某些生理功能。了解哪些mirna参与了这种细胞间串扰，以及它们在特定环境条件下如何发挥作用，对于获得细胞间通信的新视角至关重要。生物技术的进步已经产生了大量的转录组学数据，这些数据激发了有效的计算策略来理解细胞-细胞相互作用中的mirna，这是建模生物系统的基础。这个研究细胞-细胞相互作用中的mirna的项目将产生方法和工具，这些方法和工具将免费提供给科学界。该研究将纳入研究生、本科生和中小学教育，并将传播给研究界和公众，以增进科学认识。该项目旨在整合大规模转录组学数据，并创建有效的计算算法来模拟不同条件下与细胞-细胞相互作用相关的miRNA活性。与细胞-细胞相互作用相关的miRNA活性的先进统计算法和概率模型有望揭示miRNA在细胞通信和表型形成中的各种作用。这项研究不仅有望促进对细胞通信的科学理解，而且还将激发人们在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。该项目的成果将通过项目网站（http://hulab.ucf.edu/research/projects/cell2cell/）.This)公布，该奖项反映了美国国家科学基金会的法定使命，并通过基金会的智力价值和更广泛的影响审查标准进行评估，认为值得支持。

Cell to cell Interactions are essential for the overall function of multicellular organisms. Recent studies have discovered that non-coding microRNAs (miRNAs) can be transferred from one cell to another cell to perform certain physiological functions. Understanding which miRNAs participate in this intercellular crosstalk and how they function under specific environmental conditions is essential to gaining a new perspective of intercellular communications. Biotechnology advancement has generated a large amount of transcriptomics data that motivate efficient computational strategies to understand miRNAs in cell-cell interactions, which is fundamental to modeling biological systems. This project investigation miRNAs in cell-cell interactions will generate methods and tools that will be freely available to the scientific community. The research will be incorporated into graduate, undergraduate and K-12 education, and will be disseminated to the research community and the public to enhance scientific understanding. The project seeks to integrate large-scale transcriptomics data and create efficient computational algorithms to model miRNA activities relevant to cell-cell interactions under different conditions. The advanced statistical algorithms and probabilistic models of miRNA activities related to cell-cell interactions promise to unveil various roles of miRNAs in cell communications and phenotype formulation. The research is expected to not only advance scientific understanding of cell communications but also stimulate interest in developing and advancing efficient computational modeling and data integration methods in the informatics research field. Outputs of the project will be made available through the project website (http://hulab.ucf.edu/research/projects/cell2cell/).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.