Unknown

Dataset Information

0

A Large-Scale Gene Expression Intensity-Based Similarity Metric for Drug Repositioning.


ABSTRACT: Biological systems often respond to a specific environmental or genetic perturbation without pervasive gene expression changes. Such robustness to perturbations, however, is not reflected on the current computational strategies that utilize gene expression similarity metrics for drug discovery and repositioning. Here we propose a new expression-intensity-based similarity metric that consistently achieved better performance than other state-of-the-art similarity metrics with respect to the gold-standard clustering of drugs with known mechanisms of action. The new metric directly emphasizes the genes exhibiting the greatest changes in expression in response to a perturbation. Using the new framework to systematically compare 3,332 chemical and 3,934 genetic perturbations across 10 cell types representing diverse cellular signatures, we identified thousands of recurrent and cell type-specific connections. We also experimentally validated two drugs identified by the analysis as potential topoisomerase inhibitors. The new framework is a valuable resource for hypothesis generation, functional testing, and drug repositioning.

SUBMITTER: Huang CT 

PROVIDER: S-EPMC6135902 | biostudies-other | 2018 Sep

REPOSITORIES: biostudies-other

altmetric image

Publications

A Large-Scale Gene Expression Intensity-Based Similarity Metric for Drug Repositioning.

Huang Chen-Tsung CT   Hsieh Chiao-Hui CH   Oyang Yen-Jen YJ   Huang Hsuan-Cheng HC   Juan Hsueh-Fen HF  

iScience 20180823


Biological systems often respond to a specific environmental or genetic perturbation without pervasive gene expression changes. Such robustness to perturbations, however, is not reflected on the current computational strategies that utilize gene expression similarity metrics for drug discovery and repositioning. Here we propose a new expression-intensity-based similarity metric that consistently achieved better performance than other state-of-the-art similarity metrics with respect to the gold-s  ...[more]

Similar Datasets

| S-EPMC5391732 | biostudies-literature
| S-EPMC4422192 | biostudies-literature
| S-EPMC4783079 | biostudies-literature
| S-EPMC3820513 | biostudies-literature
| S-EPMC9917231 | biostudies-literature
| S-EPMC4496667 | biostudies-literature
| S-EPMC5847522 | biostudies-literature
| S-EPMC4227259 | biostudies-literature
| S-EPMC4175719 | biostudies-literature
| S-EPMC3361142 | biostudies-literature