Abstract: A feature engineering engine is included in an analytics application provided to at least one subscriber from a plurality of subscribers. The feature engineering engine generates a reduced discovery dataset based on an input dataset and stores at least a portion of the reduced discovery dataset in cache memory associated with the analytics application. While displaying at least a portion of the reduced discovery dataset, the feature engineering engine performs one or more entity resolution operations and generates an instantiated set of features. In some embodiments, the instantiated set of features is generated based on a previously generated, reusable feature definition. In some embodiments, using the instantiated set of features, a trained machine learning model is automatically selected from a plurality of models based on a performance metric determined for the instantiated set of features.

Abstract: Described herein are methods and kits for performing plasmon-enhanced fluoro-dot assays. These assays enable observing a correlation between a chemical stimulus and a biological response of cultured cells in vitro.