图 书 馆
用于基因组数据融合的核方法Kernel methods for genomic data fusion |
|
| 课程网址: | http://videolectures.net/mlsb2012_moreau_kernel/ |
| 主讲教师: | Yves Moreau |
| 开课单位: | 鲁汶大学 |
| 开课时间: | 2012-10-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Despite significant advances in omics techniques, the identification of genes causing rare genetic diseases and the understanding of the molecular networks underlying those disorders remains difficult. Gene prioritization attempts to integrate multiple, heterogeneous data sources to identify candidate genes most likely to be associated with or causative for a disorder. Such strategies are useful both to support clinical genetic diagnosis and to speed up biological discovery. Genomic data fusion algorithms are rapidly maturing statistical and machine learning techniques have emerged that integrate complex, heterogeneous information (such as sequence similarity, interaction networks, expression data, annotation, or biomedical literature) towards prioritization, clustering, or prediction. In this talk, we will focus in particular on kernel methods and will propose several strategies for prioritization and clustering in particular. We also go beyond learning methods as such by addressing how such strategies can be embedded into the daily practice of geneticists, mostly through collaborative knowledge bases that integrate tightly with prioritization and network analysis methods. |
| 关 键 词: | 组学技术; 基因优先化; 遗传疾病 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-07-02：cwx |
| 阅读次数: | 43 |