Nature ProtocolsBioinformaticsPeer-reviewed journal article
OCTAD: an open workplace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features
Billy ZengiD, Benjamin Scott GlicksbergiD, Patrick A. NewburyiD, Evgeny Chekalin, Jing XingiD, Ke LiuiD, Anita WeniD, Caven Chow, Bin CheniD
Abstract
One approach to precision medicine is to discover drugs that target molecularly defined diseases. Voluminous cancer patient gene expression profiles have been accumulated in public databases, enabling the creation of a cancer-specific expression signature. By matching this signature to perturbagen-induced gene expression profiles from large drug libraries, researchers can prioritize small molecules that present high potency to reverse expression of signature genes for further experimental testing of their efficacy. This approach has proven to be an efficient and cost-effective way to identify efficacious drug candidates. However, the success of this approach requires multiscale procedures, imposing significant challenges to many labs. Therefore, we present OCTAD: an open workplace for virtually screening compounds targeting precise cancer patient groups using gene expression features. We release OCTAD as a web portal and standalone R workflow to allow experimental and computational scientists to easily navigate the tool. In this work, we describe this tool and demonstrate its potential for precision medicine.
- organism: human
- assay: bulk RNA-seq
- research focus: drug response / drug discovery
- research focus: benchmarking
- research focus: database / resource
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 48
- FWCI
- 4.71
- Field percentile
- top 4%
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