Design and development of efficient algorithms for RNA interaction structure prediction

动机：直到最近，RNA分子被认为仅仅是将信息从DNA传递到蛋白质的信使。RNA现在被认为在所有水平的细胞活动中发挥积极作用，通过与细胞中的其他RNA和/或蛋白质复合物相互作用发挥其功能。在98%的人类基因组中，这些相互作用的功能机制尚未得到很好的理解。这方面的进展将从根本上扩大我们对细胞功能的理解，并改变我们目前对生物学和医学的理解。 目的：本程序旨在开发一套用于类细胞系统中RNA结构预测的算法。这种精确而廉价的计算套件对于探索细胞中RNA相互作用的功能机制是理想的，并将促进我们对RNA-RNA和RNA-Protein相互作用的结构机制的理解。为此，我们将设计和开发有效和准确的通用算法，用于预测： (I)通过遵循结构的概率视图并结合可用的实验信息，更精确地观察复杂的RNA结构。 (II)复杂的RNA-RNA相互作用，包含来自各种来源的信息，适用于目前较少了解的长非编码RNA。 (III)复杂和动态的RNA-蛋白质相互作用结合了不同的信息层，以降低高计算成本并提高准确性。 影响：该研究计划将有助于解决生物学中长期存在的复杂问题，这些问题影响计算机科学，生物学，医学科学，生物化学，生物医学工程和药物基因组学研究领域的大型和多样化社区，并且是一个更大的合作的基石，该合作包括维多利亚大学，GenoLogics，Island Health，BC基因组科学中心，BC癌症机构、不列颠哥伦比亚省大学、西蒙弗雷泽大学以及当地和国家生物技术产业。它将为不列颠哥伦比亚省维多利亚的HQP提供一个独特的跨学科培训环境，并最终使加拿大受益。我们注意到，最近与这一提议有关的发现改变了我们对细胞功能的理解，并获得了诺贝尔奖。

Motivation: Until recently RNA molecules were considered as merely the messenger to transfer information from DNA to protein. RNA is now believed to play an active role in all levels of cellular activity, exerting its function through interaction with other RNAs and/or protein complexes in the cell. The mechanism of function of these interactions in 98% of the human genome is not yet well understood. Advances on this front will fundamentally expand our understanding of cellular function and transform our current understandings in biology and medical sciences. Objective: This program aims to develop a suite of algorithms for RNA structure prediction in cell-like systems. This accurate and inexpensive computational suite will be desirable for probing the mechanism of function of RNA interaction in the cell, and will advance our understanding of structural mechanisms of RNA-RNA and RNA-Protein interaction. To this end we will design and develop efficient and accurate general-purpose algorithms for prediction of: (I) A more precise view of the complex RNA structure by following a probabilistic view of the structure and incorporating available experimental information. (II) Complex RNA-RNA interaction incorporating information from various sources and applicable to currently less-understood long non-coding RNAs. (III) Complex and dynamic RNA-Protein interactions incorporating different layers of information to reduce high computational cost and increase accuracy. Impact: This research program will contribute to resolving long-standing and complex questions in biology that impact a large and diverse community of research fields computer science, biology, medical sciences, biochemistry, biomedical engineering, and pharmaco-genomics, and is a cornerstone of a larger collaboration that incorporates on- and off-campus collaborations at the University of Victoria, GenoLogics, Island Health, BC Genome Science Centre, BC Cancer Agency, University of British Columbia, Simon Fraser University, as well as local and national biotechnology industry. It will provide a unique, interdisciplinary training environment for HQP in Victoria, British Columbia and ultimately benefits Canada. We note that recent discoveries that pertain to this proposal have changed our understanding of cellular function and were awarded a Nobel Prize.