References
- Atkinson, A. C. and Donev, A. N. (1989). “The Construction of Exact D-Optimum Experimental Designs with Application to Blocking Response Surface Designs”. Biometrika 76 (3), 515–526.
- Atkinson, A.; Donev, A.; and Tobias, R. (2007). Optimum Experimental Designs, with SAS.
- Cook, R. D. and Nachtsheim, C. J. (1989). “Computer-Aided Blocking of Factorial and Response Surface Designs”. Technometrics 31, pp. 339–346.
- Goos, P. and Donev, A. N. (2006). “Blocking Response Surface Designs”. Computational Statistics and Data Analysis 51 (2), 1075–1088.
- Goos, P. and Jones, B. (2011). Optimal Design of Experiments—A Case Study Approach. Chichester, UK: John Wiley & Sons, Ltd.
- Goos, P.; Jones, B.; and Syafitri, U. (2016). “I-Optimal Design of Mixture Experiments”. Journal of the American Statistical Association 111, pp. 899–911.
- Goos, P. and Vandebroek, M. (2001). “D-Optimal Response Surface Designs in the Presence of Random Block Effects”. Computational Statistics and Data Analysis 37 (4), pp. 433–453.
- Goos, P. and Vandebroek, M. (2004). “Outperforming Completely Randomized Designs”. Journal of Quality Technology 36 (1), pp. 12.
- Jones, B. and Goos, P. (2012). “I-Optimal Versus D-Optimal Split-Plot Response Surface Designs”. Journal of Quality Technology 44 (2), pp. 85–101.
- Jones, B. and Goos, P. (2015). “Optimal Design of Blocked Experiments in the Presence of Supplementary Information About the Blocks”. Journal of Quality Technology 47 (4), pp. 301–317.
- Kokalj, T.; Perez-Ruiz, E.; and Lammertyn, J. (2015). “Building Bio-Assays with Magnetic Particles on a Digital Microfluidic Platform”. New Biotechnology 32 (5).
- Montgomery, D. C. (2012). Design and Analysis of Experiments, vol. 2. Hoboken, NJ: John Wiley & Sons, Inc.
- Otzen, D. (2011). “Protein-Surfactant Interactions: A Tale of Many States”. Biochimica et Biophysica Acta–Proteins and Proteomics 1814 (5), pp. 562–591.
- Patist, A.; Bhagwat, S. S.; Penfield, K. W.; Aikens, P.; and Shah, D. O. (2000). “On the Measurement of Critical Micelle Concentrations of Pure and Technical-Grade Nonionic Surfactants”. Journal of Surfactants and Detergents 3 (1), pp. 53–58.
- Rissin, D. M.; Kan, C. W.; Campbell, T. G.; Howes, S. C.; Fournier, D. R.; Song, L.; … Duffy, D. C. (2010). “Single-Molecule Enzyme-Linked Immunosorbent Assay Detects Serum Proteins at Subfemtomolar Concentrations”. Nature Biotechnology 28 (6), pp. 595–599.
- Rodriguez, M.; Jones, B.; Borror, C. M.; and Montgomery, D. C. (2011). “Generating and Assessing Exact G-Optimal Designs”. Journal of Quality Technology 42 (1), pp. 3–29.
- Tekin, H. C.; Cornaglia, M.; and Gijs, M. A. (2013). Ultrasensitive Protein Detection: A Case for Microfluidic Magnetic Bead-Based Assays. Lab on a Chip 13 (24), pp. 4711–4739.
- Wilson, D. H.; Hanlon, D. W.; Provuncher, G. K.; Chang, L.; Song, L.; Patel, P. P.; … Duffy, D. C. (2011). “Fifth-Generation Digital Immunoassay for Prostate-Specific Antigen by Single Molecule Array Technology”. Clinical Chemistry 57 (12), pp. 1712–1721.
- Witters, D.; Knez, K.; Ceyssens, F.; Puers, R.; and Lammertyn, J. (2013). “Digital Microfluidics-Enabled Single-Molecule Detection by Printing and Sealing Single Magnetic Beads in Femtoliter Droplets”. Lab on a Chip 13 (11), pp. 2047–2054.
- Wu, D.; Milutinovic, M. D.; and Walt, D. R. (2015). “Single Molecule Array (Simoa) Assay with Optimal Antibody Pairs for Cytokine Detection in Human Serum Samples”. The Analyst 140 (18), pp. 6277–6282.