Abstract: Systems, methods and computer-readable media are provided for identifying organisms for production. The identification is based upon determining one or more outlier detection parameters for identifying outliers (e.g., outlier wells, strains, plates holding organisms) from a data set of organism performance metrics. A prediction engine may identify one or more candidate outliers based upon a first set of outlier detection parameters (e.g., outlier detection threshold), and determine probability metrics that represent likelihoods that candidate outliers belong to an outlier class. Based on those metrics, some of the outliers may be excluded from consideration in predicting organism performance for the purpose of selecting organisms for production.

Abstract: Systems, methods and computer-readable media are provided for designing experiments for organisms at a first scale to generate first-scale performance data used in predicting performance of the organisms at a second, larger scale. The design includes determining first-scale screening conditions based at least in part upon the contribution of second-scale conditions to performance parameters of an organism at the second scale. The first-scale screening conditions include one or more proxies for second-scale conditions that cannot be replicated at first scale. The design determines first-scale screening parameters based at least in part upon computer modeling of the metabolism of the organism at the second scale.

Abstract: Systems, methods and computer-readable media storing executable instructions are provided for improving performance of an organism with respect to a phenotype of interest at a second scale based upon measurements at a first scale. First scale performance data based at least in part upon observed first performance of first organisms at a first scale and second scale performance data based at least in part upon observed second performance of second organisms at a second scale larger than the first scale are accessed. A prediction function based at least in part upon the relationship of the second scale performance data to the first scale performance data is generated. The prediction function may be applied to performance data observed for test organisms with respect to the phenotype of interest at the first scale to generate second scale predicted performance data for the test organisms at the second scale.

Abstract: Systems, methods and computer-readable media are provided for identifying organisms for production. The identification is based upon determining one or more outlier detection parameters for identifying outliers (e.g., outlier wells, strains, plates holding organisms) from a data set of organism performance metrics. A prediction engine may identify one or more candidate outliers based upon a first set of outlier detection parameters (e.g., outlier detection threshold), and determine probability metrics that represent likelihoods that candidate outliers belong to an outlier class. Based on those metrics, some of the outliers may be excluded from consideration in predicting organism performance for the purpose of selecting organisms for production.