Abstract
Connectivity mapping resources consist of signatures representing changes in cellular state following systematic small-molecule, disease, gene, or other form of perturbations. Such resources enable the characterization of signatures from novel perturbations based on similarity; provide a global view of the space of many themed perturbations; and allow the ability to predict cellular, tissue, and organismal phenotypes for perturbagens. A signature search engine enables hypothesis generation by finding connections between query signatures and the database of signatures. This framework has been used to identify connections between small molecules and their targets, to discover cell-specific responses to perturbations and ways to reverse disease expression states with small molecules, and to predict small-molecule mimickers for existing drugs. This review provides a historical perspective and the current state of connectivity mapping resources with a focus on both methodology and community implementations.
| Original language | English |
|---|---|
| Pages (from-to) | 69-92 |
| Number of pages | 24 |
| Journal | Annual review of biomedical data science |
| Volume | 2 |
| DOIs | |
| State | Published - 20 Jul 2019 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© Annual Review of Biomedical Data Science.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- drug repositioning
- network analysis
- responsome
- signature commons
- systems biology
- systems pharmacology
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