Bayesian Analysis of Two-Level Fractional Factorial Experiments with Non-Normal Responses

2013 ◽  
Vol 42 (9) ◽  
pp. 1970-1988 ◽  
Author(s):  
Jian-jun Wang ◽  
Yi-zhong Ma
Keyword(s):  
Bayesian Analysis ◽  
Fractional Factorial ◽  
Factorial Experiments

Identifying significant effects in fractional factorial experiments

1994 ◽  
Vol 8 (3) ◽  
pp. 205-219 ◽  
Author(s):  
Øyvind Langsrud ◽  
Marit Risberg Ellekjaer ◽  
Tormod Naes
Keyword(s):  
Fractional Factorial ◽  
Factorial Experiments

scholarly journals Reproducing bench-scale cell growth and productivity

2018 ◽  
Author(s):  
Ariel Hecht ◽  
James Filliben ◽  
Sarah A. Munro ◽  
Marc Salit
Keyword(s):  
Escherichia Coli ◽  
Cell Growth ◽  
Small Molecule ◽  
Fluorescent Protein ◽  
Fractional Factorial ◽  
Red Fluorescent Protein ◽  
Factorial Experiments ◽  
Minimum Information ◽  
E Coli ◽  
Product Titer

Reproducing, exchanging, comparing, and building on each other’s work is foundational to technology advances.1Advancing biotechnology calls for reliable reuse of engineered strains.2Reliable reuse of engineered strains requires reproducible growth and productivity. To demonstrate reproducibility for biotechnology, we identified the experimental factors that have the greatest effect on the growth and productivity of our engineered strains.3–6We present a draft of a Minimum Information Standard for Engineered Organism Experiments (MIEO) based on this method. We evaluated the effect of 22 factors onEscherichia coli(E. coli) engineered to produce the small molecule lycopene, and 18 factors onE. coliengineered to produce red fluorescent protein (RFP). Container geometry and shaking had the greatest effect on product titer and yield. We reproduced our results under two different conditions of reproducibility:7conditions of use (different fractional factorial experiments), and time (48 biological replicates performed on 12 different days over four months).

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