Cytometric Bead Arrays: RayPlex™

Quantitative Multiplex Bead Immunoassay

RayPlex™ Cytometric Bead Arrays enable high throughput multiplex protein detection in a wide variety of sample types with flow cytometry; thus, coupling the versatility of RayBiotech's vast antibody pair library with familiar, reliable flow cytometry methodology.

RayPlex™ utilizes the sandwich immunoassay principle, wherein a target protein is immobilized between a capture antibody on a microbead and a fluorescently-conjugated detection antibody. By using different combinations of microbead sizes and fluorophores, multiple target proteins are analyzed simultaneously. RayPlex™ is compatible with most standard flow cytometers that are equipped with blue and red lasers capable of detecting fluorescence in the phycoerythrin (PE) and allophycocyanin (APC) channels, respectively.

Features

  • Less sample, more data: up to 25 proteins can be quantified from only 25 µl or less of your precious sample
  • 4 hour processing time
  • 5-10x more cost-effective than ELISA
  • Compatible with most flow cytometers
  • No specialized or dedicated instrument(s) needed
  • Customizable – create your custom array from our list of targets

How it Works

Cytometric bead array - How it works

Contents of Kit

  • RayPlex™ Multiplex Bead Cocktail
  • 1X Assay Diluent
  • 20X Wash Buffer
  • Serum Diluent
  • Lyophilized Protein Standard Mix
  • 10X Biotinylated Detection Antibody Cocktail
  • 100X Streptavidin PE
  • Rainbow Particles
  • Extra RayPlex™ Multiplex Bead Cocktail
  • V-bottom 96-well Microplate
  • Filter 96-well Microplate

Research Applications

  • High-throughput profiling of cytokine expression
  • Validation of semi-quantitative antibody array results
  • Identifying potential molecular targets for drug development
  • Identifying the molecular mechanisms of drug action
  • Identifying crucial factors involved in disease processes
  • Discovering biomarkers for disease management
  • Discovering expression patterns for molecular classification of diseases

Representative Data

Representative data