The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
Transcriptional data: a new gateway to drug repositioning?
Open accessAbstract
Recent advances in computational biology suggest that any perturbation to the transcriptional programme of the cell can be summarised by a proper 'signature': a set of genes combined with a pattern of expression. Therefore, it should be possible to generate proxies of clinicopathological phenotypes and drug effects through signatures acquired via DNA microarray technology. Gene expression signatures have recently been assembled and compared through genome-wide metrics, unveiling unexpected drug-disease and drug-drug 'connections' by matching corresponding signatures. Consequently, novel applications for existing drugs have been predicted and experimentally validated. Here, we describe related methods, case studies and resources while discussing challenges and benefits of exploiting existing repositories of microarray data that could serve as a search space for systematic drug repositioning.
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How to improve R&D productivity: the pharmaceutical industry's grand challenge
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Drug repositioning: identifying and developing new uses for existing drugs
Ashburn, T. T., & Thor, K. B. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1468 · Cited by 3,237
Predicting new molecular targets for known drugs
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Alzheimer’s disease: Clinical trials and drug development
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The Connectivity Map: A new tool for biomedical research
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Modulatory profiling identifies mechanisms of small molecule-induced cell death
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Drug repurposing: progress, challenges and recommendations
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Self-citationPerturbation-response genes reveal signaling footprints in cancer gene expression
(2017) · doi:10.1038/s41467-017-02391-6 · Cited by 1,108
Systematic integration of biomedical knowledge prioritizes drugs for repurposing
Himmelstein, D. S., Lizee, A., Hessler, C., Brueggeman, L., Chen, S. L., Hadley, D., Green, A., Khankhanian, P., & Baranzini, S. E. (2017) · eLife · doi:10.7554/elife.26726 · Cited by 666
A survey of current trends in computational drug repositioning
Li, J., Zheng, S., Chen, B., Butte, A. J., Swamidass, S. J., & Lu, Z. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbv020 · Cited by 555
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Metadata
- Authors
- Iorio, F., Rittman, T., Ge, H., Menden, M., & Saez-Rodriguez, J.
- Venue
- Drug Discovery Today
- Publisher
- Elsevier BV
- Published
- 2013-04
- Volume
- 18
- Issue
- 7-8
- Pages
- 350-357
- ISSN
- 1359-6446 (ISSN-L)
- OpenAlex
- W1992407562
- Cited by
- 237
- References
- 9
- FWCI
- 10.86
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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