Abstract: A data-driven algorithm including various network analysis routes to characterize the production of known and putative specialized metabolites and unknown analytes triggered by different exogenous compounds. Bipartite networks quantify the relationship between metabolites and treatments stimulating their production through two routes. A direct route determines the production of known and putative specialized metabolites induced by a treatment. An auxiliary route is specific for unknown analytes. Various network centrality metrics rank treatments based on their ability to trigger a broad range of specialized metabolites. The specialized metabolites are ranked based on their receptivity to various treatments. This enables tracking the influence of any exogenous treatment or abiotic factor on metabolomics output for targeted metabolite research.

Abstract: In one implementation, products in a shopping cart are provided to a point of sale system. The products are removed from the shopping cart and scanned with a transducer system. A database association system queries a database and determines the likelihood that the scanned products are indicative of products located in a lower support unit of the shopping cart. A notification is displayed on a user interface indicating the possibility of products located in the lower support unit of the shopping cart. A user is then queried as to whether a product was located in the lower support unit and the association system is updated to reflect a revised probability that the scanned products are indicative of products located in a lower support unit of the shopping cart.