Designing experiments for high-throughput protein expression

The advent of high-throughput protein production and the vast amount of data it is capable of generating has created both new opportunities and problems. Automation and miniaturization allow experimentation to be performed more efficiently, justifying the cost involved in establishing a high-throughput platform. These changes have also magnified the need for effective statistical methods to identify trends and relationships in the data. The application of quantitative management tools to this process provides the means of ensuring maximum efficiency and productivity.