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SDRS—an algorithm for analyzing large-scale dose–response data
Summary: Dose–response information is critical to understanding drug effects, yet analytical methods for dose–response assays cannot cope with the dimensionality of large-scale screening data such as the microarray profiling data. To overcome this limitation, we developed and implemented the Sigmoid...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3187656/ https://www.ncbi.nlm.nih.gov/pubmed/21865301 http://dx.doi.org/10.1093/bioinformatics/btr489 |
Sumario: | Summary: Dose–response information is critical to understanding drug effects, yet analytical methods for dose–response assays cannot cope with the dimensionality of large-scale screening data such as the microarray profiling data. To overcome this limitation, we developed and implemented the Sigmoidal Dose Response Search (SDRS) algorithm, a grid search-based method designed to handle large-scale dose–response data. This method not only calculates the pharmacological parameters for every assay, but also provides built-in statistic that enables downstream systematic analyses, such as characterizing dose response at the transcriptome level. Availability: Bio::SDRS is freely available from CPAN (www.cpan.org). Contacts: ruiruji@gmail.com; bruc@acm.org Supplementary Information: Supplementary data is available at Bioinformatics online. |
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