确定药物靶向疾病的关键驱动因素Identifying drug-targetable key drivers of disease |
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课程网址: | http://videolectures.net/ESHGsymposium2016_franke_drug_targetable... |
主讲教师: | Lude Franke |
开课单位: | 格罗宁根大学 |
开课时间: | 2016-07-18 |
课程语种: | 英语 |
中文简介: | 在过去的几年里,全基因组关联研究已经揭示了超过10000种疾病的遗传危险因素。对于许多疾病,现在很明显有几十个变异涉及,排除了针对这些基因座中每一个致病基因的药物开发。然而,由于每种疾病这些变异通常影响有限数量的途径,因此设计策略来揭示这些疾病的“关键驱动因素”基因和途径可能会为药物干预提供线索。通过结合共调节网络(Fehrmann等人,NG 2015)、反式eQTLs(Westra等人,NG 2015)、反式meQTLs(Bonder等人,BioRXiv 2015)和新的分析方法(Descripte等人,Nature Communications 2015,Zhernakova等人,BioRXiv 2015),我们相信这些关键驱动基因可能被发现。我将讨论这些方法,并将描述我们如何使用机器学习来回答我们正在研究的问题。 |
课程简介: | In the last few years genome-wide association studies have revealed over 10,000 genetic risk factors for disease. For many disorders it is now clear that there are dozens of variants involved, precluding development of drugs that target each of the causal genes in side these loci. However, since per disease these variants typically affect a limited number of pathways, devising strategies to uncover the ‘key driver’ genes and pathways for these diseases might provide leads for pharmaceutical intervention. By combining co-regulation networks (Fehrmann et al, NG 2015), trans-eQTLs (Westra et al, NG 2015), trans-meQTLs (Bonder et al, BioRXiv 2015) and novel analytical methods (Depict et al, Nature Communications 2015, Zhernakova et al, BioRXiv 2015) we believe these key driver genes might be uncovered. I will discuss these approaches and will describe how we employ machine learning to answer the questions that we work on. |
关 键 词: | 基因; 疾病; 药物干预 |
课程来源: | 视频讲座网 |
数据采集: | 2020-12-14:yxd |
最后编审: | 2020-12-14:yxd |
阅读次数: | 62 |