Biological and Computational Complexity

生物学和计算复杂性2020-2025中的CRC旨在开发识别基因组中功能区域的方法，并在多个嵌入水平上发现功能区域之间的进化关系。具体目标是：1）建立多个RNA家族的模型以快速鉴定RNA基因; 2）在转录水平上推断编码基因之间的进化关系; 3）利用基因邻域信息校正基因树。这些结果将有助于现代计算基因组学的关键挑战，即根据基因组测序的快速进展扩大基因组注释，并为更深入地重建基因组组分的进化提供综合方法。

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.