图 书 馆
网络基因与药物：从大规模实验数据中了解基因的功能和药物作用方式Networking genes and drugs: Understanding gene function and drug mode of action from large-scale experimental data |
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| 课程网址: | http://videolectures.net/licsb2010_bernardo_igr/ |
| 主讲教师: | Diego di Bernardo |
| 开课单位: | Telethon遗传与医学研究所 |
| 开课时间: | 2010-05-03 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | A gene regulatory network, where two genes are connected if they are directly, or functionally, regulating each other, can be 'reverse-engineered' from large-scale experimental data such as gene expression profiles. Here used a simple but effective reverse-engineering approach using all the available gene expression profiles in mammals, solving along the way the problems of handling, normalizing and analysing such massive dataset. We reverse-engineered a coexpression network for Homo Sapiens (Mus Musculus) from a set of 20,255 (8895) gene expression profiles. The human (mouse) network is characterized by a set of 22283 (45101) nodes (i.e. genes) and a set of 4,817,629 (14,641,095) edges, where the edge is weighted by the Mutual Information (MI) measure between the two genes. We show how the resulting network can be then used to understand the function of a gene, the modularity of gene regulation, as well as, as a tool to analyse "gene signatures" to identify the mode of action of a drug. We will also show how it is possible to use gene expression profile to build a "drug network", where drugs can be automatically grouped in subnetworks ('communities') of drugs sharing a similar mode of action. |
| 关 键 词: | 基因调控网络; 逆向工程; 基因表达谱 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-27：lxf |
| 阅读次数: | 64 |