Biological and Computational Complexity

生物和计算复杂性

• 批准号: 1000232573-2019
• 负责人: Ouangraoua, Aida
• 金额: $ 3.64万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Canada Research Chairs
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=695563
• 关键词: Biological; Computational; Complexity

The CRC in Biological and Computational Complexity 2020-2025 aims to develop methods to identify functional regions in genomes and to discover the evolutionary relationships between functional regions at multiple embedded levels. The specific objectives are: 1) to develop models of multiple RNA families for fast identification of RNA genes, 2) to infer evolutionary relationships between coding genes at transcripts level, 3) to correct gene trees using gene neighborhood information. The results will contribute to crucial challenges of modern computational genomics, namely to scale up genome annotation to the rapid advances of genome sequencing, and to provide integrative methods for more insightful reconstructions of the evolution of genome components.

2020-2025年生物和计算复杂性的CRC旨在开发方法来识别基因组中的功能区域，并在多个嵌入水平上发现功能区域之间的进化关系。其具体目标是：1)建立多个RNA家族的模型，用于快速识别RNA基因；2)在转录水平上推断编码基因之间的进化关系；3)利用基因邻域信息修正基因树。这些结果将有助于现代计算基因组学的关键挑战，即扩大基因组注释以适应基因组测序的快速发展，并为更有洞察力地重建基因组组分的进化提供综合方法。