title: Designing Successful Proteomics Experiments.
abstract: Because proteomics experiments are so complex they can readily fail, and do so without clear cause. Using standard experimental design techniques and incorporating quality control can greatly increase the chances of success. This chapter introduces the relevant concepts and provides examples specific to proteomic workflows. Applying these notions to design successful proteomics experiments is straightforward. It can help identify failure causes and greatly increase the likelihood of inter-laboratory reproducibility.
authors.affiliation: Lawrence J. Ellison Institute for Transformative Medicine of USC, Keck School of Medicine of USC, 2250 Alcazar St. CSC-240, Los Angeles, CA, 90033, USA. ruderman@usc.edu.
authors.forename: Daniel
authors.initials: D
authors.lastname: Ruderman
mesh_terms: D015982:Bias; D040901:Proteomics / Q000379:methods* / Q000592:standards*; D011786:Quality Control; D011897:Random Allocation; D015203:Reproducibility of Results; D012107:Research Design; D012984:Software; D013223:Statistics as Topic
keywords: Bias; Design of experiments; Randomization; Variance