title: SDRS--an algorithm for analyzing large-scale dose-response data.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  Bio::SDRS is freely available from CPAN (www.cpan.org).
  
  
  BACKGROUND
  ruiruji@gmail.com; bruc@acm.org
  
  
  BACKGROUND
  Supplementary data is available at Bioinformatics online.
authors.affiliation: Department of Applied Genomics, Bristol-Myers Squibb, Princeton, NJ 08543, USA. ruiruji@gmail.com
authors.forename: Rui-Ru
authors.initials: RR
authors.lastname: Ji
authors.forename: Nathan O
authors.initials: NO
authors.lastname: Siemers
authors.forename: Ming
authors.initials: M
authors.lastname: Lei
authors.forename: Liang
authors.initials: L
authors.lastname: Schweizer
authors.forename: Robert E
authors.initials: RE
authors.lastname: Bruccoleri
mesh_terms: D000465:Algorithms; D004305:Dose-Response Relationship, Drug; D020869:Gene Expression Profiling / Q000379:methods*; D059467:Transcriptome / Q000187:drug effects*