图 书 馆
使用调控模型的基因表达测量的目标检索Targeted retrieval of gene expression measurements using regulatory models |
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| 课程网址: | http://videolectures.net/mlsb2012_georgii_retrieval/ |
| 主讲教师: | Elisabeth Georgii |
| 开课单位: | 国赫尔辛基科技机构 |
| 开课时间: | 信息不详。欢迎您在右侧留言补充。 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | **Motivation:** Large public repositories of gene expression measurements offer the opportunity to position a new experiment into the context of earlier studies. While previous methods rely on experimental annotation or global similarity of expression profiles across genes or gene sets, we compare experiments by measuring similarity based on an unsupervised, data-driven regulatory model around pre-specified genes of interest. Our experiment retrieval approach is novel in two conceptual respects: (i) targetable focus and interpretability: the analysis is targeted at regulatory relationships of genes that are relevant to the analyst or come from prior knowledge; (ii) regulatory model-based similarity measure: related experiments are retrieved based on the strength of inferred regulatory links between genes.\\ **Results:** We learn a model for the regulation of specific genes from a data repository, and exploit it to construct a similarity metric for an information retrieval task. We use the Fisher kernel, a rigorous similarity measure that typically has been applied to utilize generative models in discriminative classifiers. Results on human and plant microarray collections indicate that our method is able to substantially improve the retrieval of related experiments against standard methods. Furthermore, it allows the user to interpret biological conditions in terms of changes in link activity patterns. Our study of the osmotic stress network for A. thaliana shows that the method successfully identifies relevant relationships around given key genes.\\ |
| 关 键 词: | 机器学习; 计算机科学; 生物信息学 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-12-23：liyy |
| 阅读次数: | 33 |