The identification of drug treatments that are useful in diverse therapeutic settings is a significant driving force in biomedical research [Macarron et al., 2011], [Poureetezadi et al., 2014], [Lamb, 2007]. Typical means for measuring the efficacy of a drug for a given clinical application include protein-protein interactions, cell death, mitochondrial respiration and cell growth as well as broader measurements of absorption, distribution, metabolism, excretion and toxicity (ADMET), specifically related the the drug or drugs being tested [Szakcs et al., 2008]. A wide array of methods are routinely employed to perform these screens, from ligand binding assays [Wagner et al., 2016] to high-throughput proteomics [Verheul, 2014]. One method that is currently underutilized in small-molecule drug screens and drug discovery is high-throughput transcriptome sequencing, such as RNA-Seq. Although RNA-Seq is routinely used to profile patterns of genetic changes following perturbations such as drug treatment [Young et al., 2014], it has not, to my knowledge, yet been used as the primary readout of a drug screen.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8DV1K17 |
| Date | January 2016 |
| Creators | Ray, Forest |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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