Ensemble framework to infer large-scale causal gene regulatory networks from transcriptomic data

从转录组数据推断大规模因果基因调控网络的集成框架

• 批准号: RGPIN-2015-03654
• 负责人: HaibeKains, Benjamin
• 金额: $ 1.02万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=635180
• 关键词: Ensemble; framework; infer; large; scale

It is now established that complex biological phenotypes are not governed by single genes but instead by networks of interacting genes and gene products. As a consequence, deciphering the structure of the gene regulatory network (GRN) is crucial to further our understanding of fundamental processes in human cells. However, the mapping of molecular interactions in the intracellular realm remains the bottleneck in the pipeline to produce biological knowledge from high-throughput biological data.

现在已经确定，复杂的生物表型不是由单个基因控制的，而是由相互作用的基因和基因产物的网络控制的。因此，破译基因调控网络（GRN）的结构对于进一步了解人类细胞的基本过程至关重要。然而，细胞内领域分子相互作用的映射仍然是从高通量生物数据产生生物知识的瓶颈。